{ "cells": [ { "cell_type": "markdown", "id": "a4a3de80", "metadata": {}, "source": [ "# POlitical DIscourse Ontology Introduction" ] }, { "cell_type": "markdown", "id": "16365aa8", "metadata": {}, "source": [ "This research addresses the need for the systematic organization and integration of political discourse, regardless of the communication channels employed, whether rooted in social platforms or dissemination channels. The aim is to facilitate nuanced and advanced analyses that consider specific aspects of the political domain, including the persuasive nature of discourse, the ideological basis of the messages, the targeted audience (wether groups or comcommunities), and the temporal context of communication. The resulting ontology, named PODIO (POlitical DIscourse Ontology), offers a structured framework to enhance the understanding of political debate. It was successfully evaluated, confirming its error-free design and alignment with functional requirements. For validation, we integrated existing datasets in the Knowledge Graph from social media, news, and electoral programs, demonstrating the effectiveness of PODIO in representing diverse forms of political discourse." ] }, { "cell_type": "markdown", "id": "fc9c4bab", "metadata": {}, "source": [ "The available resources are listed bellow:\n", "- [The ontology github repository.](https://github.com/oeg-upm/PODIO)\n", "- [The ontology and the documentation.](https://w3id.org/podio)\n", "- [The Knowledge Graph.](https://w3id.org/podio/sparql)\n" ] }, { "attachments": { "image.png": { "image/png": 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" } }, "cell_type": "markdown", "id": "90896c11", "metadata": { "hide_input": true }, "source": [ "![image.png](attachment:image.png)" ] }, { "cell_type": "markdown", "id": "e0188633", "metadata": {}, "source": [ "# PODIO Knowledge Graph" ] }, { "cell_type": "markdown", "id": "68717218", "metadata": {}, "source": [ "## Generating triples" ] }, { "cell_type": "markdown", "id": "c88d9142", "metadata": { "ExecuteTime": { "end_time": "2023-12-20T19:42:50.523364Z", "start_time": "2023-12-20T19:42:50.520202Z" } }, "source": [ "You will need to install [yarrrml-parser](https://rml.io/yarrrml/tutorial/getting-started/) and download [rmlmapper-6.1.3](https://github.com/RMLio/rmlmapper-java/releases) to generate the RDF code and triples." ] }, { "cell_type": "code", "execution_count": 18, "id": "664ca44e", "metadata": { "ExecuteTime": { "end_time": "2024-02-12T11:52:33.720162Z", "start_time": "2024-02-12T11:52:33.717031Z" } }, "outputs": [], "source": [ "# This is the procedure to be used to generate the different triples.\n", "\n", "import os\n", "\n", "## Path where rmlmapper is\n", "script_path=\"/home/ibai/OEG/MadridElectoralTwitterScrapper/SeleniumTwitterScrapper/mapper/mapping_requirements\"\n", "\n", "def generate_triples(filename_mappings, verbose=False):\n", " ### Generate turtle file\n", " os.system(f\"yarrrml-parser -i {filename_mappings}.yml -o {filename_mappings}.ttl\")\n", " ### Generate triples\n", " if verbose:\n", " os.system(f\"java -jar {script_path}/rmlmapper-6.1.3-r367-all.jar -v -m {filename_mappings}.ttl -o {filename_mappings}.nt\")\n", " else:\n", " os.system(f\"java -jar {script_path}/rmlmapper-6.1.3-r367-all.jar -m {filename_mappings}.ttl -o {filename_mappings}.nt\")\n", "\n", " return \"Triples Generated\"" ] }, { "cell_type": "markdown", "id": "e52e363f", "metadata": { "heading_collapsed": true }, "source": [ "### Party Manifestos and Political Proposals" ] }, { "cell_type": "markdown", "id": "9ee5656a", "metadata": { "hidden": true }, "source": [ "Among the datasets of party manifestos available online, the most relevant we have found are:\n", "\n", "Description|Dataset\n", "---|---\n", "**USA elections party manifestos**| Woolley, J. T., Peters, G. & University Of California, S. B. (1999) The American Presidency Project. Santa Barbara, Calif.: University of California. [Web.] Retrieved from the Library of Congress, https://lccn.loc.gov/2005616760.\n", "**USA States elections party manifestos** | Hopkins, Daniel J; Coffey, Daniel J; Galvin, Daniel J; Gamm, Gerald; Henderson, John; Paddock, Joel W.; Schickler, Eric, 2022, \"Select American State Party Platforms, 1846-2017\", https://doi.org/10.7910/DVN/KNOSHL, Harvard Dataverse, V1\n", "**Scottish elections party manifestos** | Greene, Zachary; McMillan, Fraser, 2020, \"Scottish Party Election Manifestos, 1999-2016\", https://doi.org/10.7910/DVN/PH8XZO, Harvard Dataverse, V1\n", "**German local elections party manifestos** | Gross, M., & Jankowski, M. (2019). Dimensions of political conflict and party positions in multi-level democracies: evidence from the Local Manifesto Project. In West European Politics (Vol. 43, Issue 1, pp. 74–101). Informa UK Limited. https://doi.org/10.1080/01402382.2019.1602816\n", "**Spanish regional elections party manifestos** | Alonso, S., Gómez, B., & Cabeza, L. (2013). Measuring Centre–Periphery Preferences: The Regional Manifestos Project. In Regional & Federal Studies (Vol. 23, Issue 2, pp. 189–211). Informa UK Limited. https://doi.org/10.1080/13597566.2012.754351\n", "**European elections party manifestos** | Schmitt, Hermann, & Wüst, Andreas M. (2012). Euromanifestos Project (EMP) 1979 - 2004. GESIS Data Archive, Cologne. ZA4457 Data file Version 1.0.0, https://doi.org/10.4232/1.4457.\n" ] }, { "cell_type": "markdown", "id": "ea4f269b", "metadata": { "hidden": true }, "source": [ "To meet the competency questions we will reuse USA elections party manifestos from 2020 and 2016. This implies that we will use the 2020 and 2016 Democratic party manifestos and the 2016 Republican party manifesto. This is because there is no new party platform for republican party in 2020 elections, they reuse the 2016 manifesto: [*\"RESOLVED, That the 2020 Republican National Convention will adjourn without adopting a new platform until the 2024 Republican National Convention;\"*](https://www.presidency.ucsb.edu/documents/resolution-regarding-the-republican-party-platform)\n", "\n", "Party manifestos are replete of policy proposals such as the following: *Democrats will aggressively enforce non-discrimination protections in the Americans with Disabilities Act and other civil rights laws, especially when designing emergency management systems and new facilities and services in response to the pandemic. Democrats will prohibit unjustified segregation of patients with disabilities, and additionally prohibit rationing of health care that refuses or diverts hospitalization, treatment, or supplies based on a patient's disability. We recognize people with disabilities living in group homes and other care facilities are at greater risk of contracting COVID-19, and that people with disabilities may require additional resources to protect their health, well-being, and independence during the pandemic. We will improve oversight and expand protections for residents and staff at nursing homes, which have seen some of the worst COVID-19 outbreaks. And we will expand support for telemedicine, so Americans do not have to go without essential health care during the pandemic.*\n", "\n", "Extracting the policy proposals with granularity and precision is a complicated task. Whereas in other party manifestos it is easier because the proposals are numbered, in the US elections manifestos this is not the case. In order to populate the KG, we decided to generalise and take every paragraph of the party manifesto as a policy proposal. " ] }, { "cell_type": "code", "execution_count": null, "id": "b1fa99d6", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T16:57:05.876944Z", "start_time": "2024-02-06T16:57:03.534104Z" }, "code_folding": [], "hidden": true, "scrolled": false }, "outputs": [], "source": [ "# Downloading the Manifestos, aggregate with metadata and save them as JSON\n", "from bs4 import BeautifulSoup\n", "import requests, json, os\n", "\n", "## Set filenames (WITHOUT extension)\n", "if not os.path.exists(\"data\"): os.mkdir(\"data\")\n", "filename_manifestos= \"data/manifestos\"\n", "filename_proposals= \"data/proposals\"\n", "\n", "## Download the manifestos from the web and aggregate with extra data\n", "manifestos= {}\n", "pmanifestos= [\"2020-democratic-party-platform\", \"2016-democratic-party-platform\", \"2016-republican-party-platform\"]\n", "for pmanifesto in pmanifestos:\n", " response = requests.get(f'https://www.presidency.ucsb.edu/documents/{pmanifesto}')\n", " assert(response.status_code==200)\n", "\n", " soup = BeautifulSoup(response.content, 'html.parser')\n", " content= soup.find('div', class_='field-docs-content').text\n", " manifestos[pmanifesto]= {\"date\": f\"{pmanifesto.split('-')[0]}-1-1T00:00:00\", \n", " \"pparty_id\": f'{pmanifesto.split(\"-\")[1]}Party',\n", " \"source\": f'https://www.presidency.ucsb.edu/documents/{pmanifesto}',\n", " \"language\": \"http://id.loc.gov/vocabulary/iso639-2/eng\",\n", " \"content\": content}\n", "\n", "manifestos[\"2020-democratic-party-platform\"][\"pparty\"]= \"http://www.wikidata.org/entity/Q29552\"\n", "manifestos[\"2020-democratic-party-platform\"][\"ideology\"]= \"http://www.wikidata.org/entity/Q16152203\"\n", "manifestos[\"2020-democratic-party-platform\"][\"candidate\"]= \"http://www.wikidata.org/entity/Q6279\"\n", "manifestos[\"2020-democratic-party-platform\"][\"party_wikidata_id\"]= \"Q29552\"\n", "manifestos[\"2020-democratic-party-platform\"][\"candidate_wikidata_id\"]= \"Q6279\"\n", "\n", "\n", "\n", "manifestos[\"2016-democratic-party-platform\"][\"pparty\"]= \"http://www.wikidata.org/entity/Q29552\"\n", "manifestos[\"2016-democratic-party-platform\"][\"ideology\"]= \"http://www.wikidata.org/entity/Q16152203\"\n", "manifestos[\"2016-democratic-party-platform\"][\"candidate\"]= \"http://www.wikidata.org/entity/Q6294\"\n", "manifestos[\"2016-democratic-party-platform\"][\"party_wikidata_id\"]= \"Q29552\"\n", "manifestos[\"2016-democratic-party-platform\"][\"candidate_wikidata_id\"]= \"Q6294\"\n", "\n", "\n", "manifestos[\"2016-republican-party-platform\"][\"pparty\"]= \"http://www.wikidata.org/entity/Q29468\"\n", "manifestos[\"2016-republican-party-platform\"][\"ideology\"]= \"http://www.wikidata.org/entity/Q7169\"\n", "manifestos[\"2016-republican-party-platform\"][\"candidate\"]= \"http://www.wikidata.org/entity/Q22686\"\n", "manifestos[\"2016-republican-party-platform\"][\"party_wikidata_id\"]= \"Q29468\"\n", "manifestos[\"2016-republican-party-platform\"][\"candidate_wikidata_id\"]= \"Q22686\"\n", "\n", "\n", "manifestos[\"2020-republican-party-platform\"]= manifestos[\"2016-republican-party-platform\"].copy()\n", "manifestos[\"2020-republican-party-platform\"][\"date\"]= \"2020-1-1T00:00:00\"\n", "pmanifestos.append(\"2020-republican-party-platform\")\n", "\n", "## Save manifestos data\n", "with open(f\"{filename_manifestos}.json\", \"w\") as f:\n", " json.dump(manifestos, f)\n", "\n", "## Extract policy proposals from manifestos\n", "policy_proposals= []\n", "for pmanifesto in pmanifestos:\n", " proposals= [x for x in manifestos[pmanifesto][\"content\"].split(\"\\n\") if x != \"\"]\n", " counter= 0\n", " for proposal in proposals:\n", " counter += 1\n", " if pmanifesto.split(\"-\")[1] == \"republican\": \n", " author= \"http://www.wikidata.org/entity/Q29468\"\n", " ideology= \"http://www.wikidata.org/entity/Q7169\"\n", " else: \n", " author=\"http://www.wikidata.org/entity/Q29552\"\n", " ideology= \"http://www.wikidata.org/entity/Q16152203\"\n", " proposal_json= {\n", " \"id\": counter,\n", " \"date\": f\"{pmanifesto.split('-')[0]}-1-1T00:00:00\", \n", " \"language\": \"http://id.loc.gov/vocabulary/iso639-2/eng\",\n", " \"content\": proposal, \n", " \"source\": f'https://www.presidency.ucsb.edu/documents/{pmanifesto}',\n", " \"word_count\": len(proposal.split()),\n", " \"part_of\": f'{pmanifesto.split(\"-\")[1]}Party',\n", " \"target\": \"http://www.wikidata.org/entity/Q846570\",\n", " \"ideology\": ideology, \n", " \"creator\": author,\n", " \"publisher\": author\n", " }\n", " policy_proposals.append(proposal_json)\n", "\n", "## Save policy proposals data\n", "with open(f\"{filename_proposals}.json\", \"w\") as f:\n", " json.dump(policy_proposals, f)" ] }, { "cell_type": "code", "execution_count": null, "id": "5f94501a", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T16:57:30.037738Z", "start_time": "2024-02-06T16:57:05.878173Z" }, "code_folding": [ 8, 31, 35 ], "hidden": true }, "outputs": [], "source": [ "# Generate the data mapping file to transform the above data into triples\n", "import os\n", "\n", "## Set filenames (WITHOUT extension)\n", "filename_mappings= \"mappings/mappings_manifestos\"\n", "if not os.path.exists(\"mappings\"): os.mkdir(\"mappings\")\n", "\n", "## Generate mapping file according to the JSONs data\n", "mapping= f\"\"\"\n", "prefixes:\n", " #Core imports\n", " rdf: \"http://www.w3.org/1999/02/22-rdf-syntax-ns#\"\n", " rdfs: \"http://www.w3.org/2000/01/rdf-schema#\"\n", " xsd: \"http://www.w3.org/2001/XMLSchema#\"\n", " xml: \"http://www.w3.org/XML/1998/namespace\"\n", " #Vocabulary imports\n", " schema: \"http://schema.org/\"\n", " terms: \"http://purl.org/dc/terms/\"\n", " dc: \"http://purl.org/dc/elements/1.1/\"\n", " dcam: \"http://purl.org/dc/dcam/\"\n", " vann: \"http://purl.org/vocab/vann/\"\n", " skos: \"http://www.w3.org/2004/02/skos/core#\"\n", " #Ontology imports\n", " owl: \"http://www.w3.org/2002/07/owl#\"\n", " foaf: \"http://xmlns.com/foaf/0.1/\"\n", " sioc: \"http://rdfs.org/sioc/ns#\"\n", " lkg: \"http://lkg.lynx-project.eu/def/\"\n", " nif: \"http://persistence.uni-leipzig.org/nlp2rdf/ontologies/nif-core#\"\n", " eli: \"http://data.europa.eu/eli/ontology#\"\n", " #Knowledge graph domain declaration\n", " podio: \"http://w3id.org/podio#\" # URL to ontoology\n", "\n", "sources:\n", " manifestos_json: [{filename_manifestos}.json~jsonpath, \"$.[*]\"]\n", " proposals_json: [{filename_proposals}.json~jsonpath, \"$.[*]\"]\n", "\n", "mappings:\n", " Manifestos:\n", " sources: \n", " - manifestos_json\n", " s: podio:PartyManifesto/USA/$(pparty_id)/$(date)\n", " po:\n", " - [a, podio:PartyManifesto]\n", " - [terms:language, $(language)~iri]\n", " - [terms:created, $(date), xsd:dateTime]\n", " - [terms:source, $(source)~iri]\n", " - [terms:publisher, $(pparty)~iri]\n", " - [podio:content, $(content), xsd:string]\n", " - [podio:ideology, $(ideology)~iri]\n", " - [podio:proposesCandidate, $(candidate)~iri]\n", "\n", " Proposals:\n", " sources: \n", " - proposals_json\n", " s: podio:PolicyProposal/USA/$(part_of)/$(date)/$(id)\n", " po:\n", " - [a, podio:PolicyProposal]\n", " - [terms:language, $(language)~iri]\n", " - [terms:created, $(date), xsd:dateTime]\n", " - [terms:source, $(source)~iri]\n", " - [terms:identifier, $(id), xsd:int]\n", " - [podio:ideology, $(ideology)~iri]\n", " - [podio:content, $(content), xsd:string]\n", " - [schema:wordCount, $(word_count)]\n", " - [terms:publisher, $(publisher)~iri]\n", " - [terms:creator, $(creator)~iri]\n", " - [podio:hasTarget, $(target)~iri]\n", " - [terms:isPartOf, podio:PartyManifesto/USA/$(part_of)/$(date)~iri]\n", " \n", " AgentCandidate:\n", " sources: \n", " - manifestos_json\n", " s: $(candidate)\n", " po:\n", " - [a, foaf:Agent]\n", " - [terms:identifier, $(candidate_wikidata_id), xsd:string]\n", " - [rdfs:isDefinedBy, $(candidate)~iri]\n", " \n", " AgentParty:\n", " sources: \n", " - manifestos_json\n", " s: $(pparty)\n", " po:\n", " - [a, foaf:Agent]\n", " - [terms:identifier, $(party_wikidata_id), xsd:string]\n", " - [rdfs:isDefinedBy, $(pparty)~iri]\n", "\"\"\"\n", "\n", "## Save mappings file\n", "with open(f\"{filename_mappings}.yml\", \"w\") as f:\n", " f.write(mapping)\n", " \n", "## Generate the triples\n", "generate_triples(filename_mappings)\n", "\n", "print(\"Political Party Manifestos Triples Generated\")" ] }, { "cell_type": "markdown", "id": "a6a89168", "metadata": {}, "source": [ "### Social Media Posts" ] }, { "cell_type": "markdown", "id": "f71044ba", "metadata": {}, "source": [ "Among the datasets of political social media posts available online, the most relevant we have found are:\n", "\n", "Social Media | Description | Dataset\n", "--- | --- | ---\n", "Facebook | **2019 Spanish General Elections Facebook Ads** | Baviera Puig, T. (2020). 2019 Spanish General Elections Facebook Ads Dataset. Universitat Politècnica de València. https://doi.org/10.4995/Dataset/10251/146502\n", "Twitter | **Spanish political parties tweets** | https://www.kaggle.com/datasets/ricardomoya/tweets-poltica-espaa/data\n", "Twitter | **Trump Tweets as of June 2020** | https://www.kaggle.com/datasets/austinreese/trump-tweets/data\n", "Twitter | **Bidedn Tweets in 2019 and 2020** | https://www.kaggle.com/datasets/akashdusane/joe-biden-tweets-us-elections\n", "\n", "To show the ability to work with different social networks we will include data from both Twitter and Facebook. In addition, we will include posts from two different countries to demonstrate that PODIO is able to correctly represent the international political discourse. This knowledge will be exploited with SPARQL queries.\n", "\n", "As many datasets are from Kaggle, you need to install [kaggle](https://pypi.org/project/kaggle/) library and get a free API key, see the [kaggle documentation](https://www.kaggle.com/docs/api) for more information about this. " ] }, { "cell_type": "code", "execution_count": 30, "id": "5d57024f", "metadata": { "ExecuteTime": { "end_time": "2024-02-12T12:00:34.331589Z", "start_time": "2024-02-12T12:00:27.417066Z" }, "code_folding": [] }, "outputs": [ { "data": { "text/plain": [ "4605002" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Data set downloading\n", "import kaggle\n", "import requests\n", "import os \n", "\n", "if not os.path.exists(\"data\"): os.mkdir(\"data\")\n", "\n", "## https://www.kaggle.com/docs/api\n", "kaggle.api.authenticate\n", "\n", "## Spanish political parties tweets\n", "kaggle.api.dataset_download_files('ricardomoya/tweets-poltica-espaa', path='data/', unzip=True)\n", "\n", "## Trump Tweets as of June 2020\n", "kaggle.api.dataset_download_files(\"austinreese/trump-tweets\", path='data/', unzip=True)\n", "\n", "## Bidedn Tweets in 2019 and 2020\n", "kaggle.api.dataset_download_files(\"akashdusane/joe-biden-tweets-us-elections\", path='data/', unzip=True)\n", "\n", "## 2019 Spanish General Elections Facebook Ads\n", "response = requests.get(\"https://riunet.upv.es/bitstream/handle/10251/146502/Facebook_Ads_2019_Spanish_General_Elections.csv?sequence=1&isAllowed=y\")\n", "open(\"data/facebook_ads.csv\", \"w\").write(response.content.decode('utf-16'))\n" ] }, { "cell_type": "code", "execution_count": 31, "id": "bb443c3f", "metadata": { "ExecuteTime": { "end_time": "2024-02-12T12:00:36.281706Z", "start_time": "2024-02-12T12:00:34.333174Z" }, "code_folding": [], "scrolled": true }, "outputs": [], "source": [ "# Data sets loading, cleaning, enriching and storage\n", "import pandas as pd\n", "from datetime import datetime\n", "import re, json\n", "\n", "## Set filenames (WITHOUT extension)\n", "filename_all_data= \"data/conversational\"\n", "filename_extra_data= \"data/conversational_extra\"\n", "filename_metrics_data= \"data/conversational_metrics\"\n", "\n", "## Limit to avoid overloading the graph database due to excessive volume of data sets.\n", "limit=4000 #If you do not want limit set as None\n", "\n", "## Dataset loading\n", "df_spain_facebook_ads= pd.read_csv(\"data/facebook_ads.csv\", sep=';', on_bad_lines='skip')[:limit]\n", "df_spain_tweets= pd.read_csv(\"data/tweets_politica_kaggle.csv\", sep='\\t', on_bad_lines='skip')[:limit]\n", "df_trump_tweets= pd.read_csv(\"data/realdonaldtrump.csv\", sep=',', on_bad_lines='skip')[:limit]\n", "df_biden_tweets= pd.read_csv(\"data/JoeBiden_Tweets_2019-20.csv\", sep=',', on_bad_lines='skip')[:limit]\n", "\n", "## Manual entity linking\n", "wikidata_ideology= {\"izquierdaunida\": \"http://www.wikidata.org/entity/Q121254\",\n", " \"ciudadanos\": \"http://www.wikidata.org/entity/Q6216\",\n", " \"ciudadanoscs\": \"http://www.wikidata.org/entity/Q6216\",\n", " \"psoe\": \"http://www.wikidata.org/entity/Q821102\",\n", " \"PSOE\": \"http://www.wikidata.org/entity/Q821102\",\n", " \"partidopopular\": \"http://www.wikidata.org/entity/Q617609\",\n", " \"pp\": \"http://www.wikidata.org/entity/Q617609\",\n", " \"podemos\": \"http://www.wikidata.org/entity/Q275595\",\n", " \"PODEMOS\": \"http://www.wikidata.org/entity/Q275595\",\n", " \"ppopular\": \"http://www.wikidata.org/entity/Q617609\",\n", " \"voxespaña\": \"http://www.wikidata.org/entity/Q948731\",\n", " \"vox\": \"http://www.wikidata.org/entity/Q948731\",\n", " \"vox_es\": \"http://www.wikidata.org/entity/Q948731\",\n", " \"realdonaldtrump\": \"http://www.wikidata.org/entity/Q31838499\",\n", " \"joebiden\": \"http://www.wikidata.org/entity/Q16152203\"}\n", "\n", "wikidata_agent= { \"izquierdaunida\": \"http://www.wikidata.org/entity/Q623740\",\n", " \"ciudadanos\": \"http://www.wikidata.org/entity/Q1393123\",\n", " \"ciudadanoscs\": \"http://www.wikidata.org/entity/Q1393123\",\n", " \"psoe\": \"http://www.wikidata.org/entity/Q138198\",\n", " \"PSOE\": \"http://www.wikidata.org/entity/Q138198\",\n", " \"partidopopular\": \"http://www.wikidata.org/entity/Q185088\",\n", " \"podemos\": \"http://www.wikidata.org/entity/Q16059622\",\n", " \"PODEMOS\": \"http://www.wikidata.org/entity/Q16059622\",\n", " \"pp\": \"http://www.wikidata.org/entity/Q185088\",\n", " \"ppopular\": \"http://www.wikidata.org/entity/Q185088\",\n", " \"voxespaña\": \"http://www.wikidata.org/entity/Q15630787\",\n", " \"vox\": \"http://www.wikidata.org/entity/Q15630787\",\n", " \"vox_es\": \"http://www.wikidata.org/entity/Q15630787\",\n", " \"realdonaldtrump\": \"http://www.wikidata.org/entity/Q22686\",\n", " \"joebiden\": \"http://www.wikidata.org/entity/Q6279\"}\n", "\n", "twitter_accounts= {\n", " \"psoe\": \"PSOE\",\n", " \"vox\": \"vox_es\",\n", " \"ciudadanos\": \"CiudadanosCs\",\n", " \"pp\": \"ppopular\",\n", " \"podemos\": \"PODEMOS\"\n", "}\n", "\n", "## Regular expresion for extracting social media specific data\n", "pattern_twitter_mentions= r'(?<=[^\\w!])@(\\w+)\\b'\n", "pattern_facebook_mentions = r'(?<=[^\\w!])@([A-Z][a-z0-9]*\\s?(?:[A-Z][a-z0-9]*)*)\\b'\n", "pattern_hashtag = r'(?!\\s)#([A-Za-z]\\w*)\\b'\n", "pattern_links= r'(?:http|ftp|https):\\/\\/(?:[\\w_-]+(?:(?:\\.[\\w_-]+)+))(?:[\\w.,@?^=%&:\\/~+#-]*[\\w@?^=%&\\/~+#-])'\n", "\n", "## Dataset specific operations: cleaning and enriching\n", "df_spain_tweets.drop(['cuenta'], axis=1, inplace=True)\n", "df_spain_tweets.rename(columns = {'timestamp':'date'}, inplace = True) \n", "df_spain_tweets.rename(columns = {'tweet':'content'}, inplace = True) \n", "df_spain_tweets.rename(columns = {'partido':'account'}, inplace = True) \n", "df_spain_tweets[\"account\"]= [x.replace(\" \",\"\") for x in df_spain_tweets[\"account\"]]\n", "df_spain_tweets[\"account\"]= [twitter_accounts[x] for x in df_spain_tweets[\"account\"]]\n", "df_spain_tweets[\"date\"]= [str(datetime.fromtimestamp(row).isoformat()) for row in df_spain_tweets[\"date\"]]\n", "df_spain_tweets[\"mentions\"]= [re.findall(pattern_twitter_mentions, str(text), re.IGNORECASE) for text in df_spain_tweets[\"content\"]]\n", "df_spain_tweets[\"hashtags\"]= [re.findall(pattern_hashtag, str(text), re.IGNORECASE) for text in df_spain_tweets[\"content\"]]\n", "df_spain_tweets[\"links\"]= [re.findall(pattern_links, str(text), re.IGNORECASE) for text in df_spain_tweets[\"content\"]]\n", "df_spain_tweets[\"agent\"]= [wikidata_agent[x.lower()] for x in df_spain_tweets[\"account\"]]\n", "df_spain_tweets[\"ideology\"]= [wikidata_ideology[x.lower()] for x in df_spain_tweets[\"account\"]]\n", "df_spain_tweets[\"media\"]=[\"Twitter\" for x in range(df_spain_tweets.shape[0])]\n", "df_spain_tweets[\"media_url\"]=[\"https://twitter.com/\" for x in range(df_spain_tweets.shape[0])]\n", "df_spain_tweets[\"source\"]=[\"https://www.kaggle.com/datasets/ricardomoya/tweets-poltica-espaa\" for x in range(df_spain_tweets.shape[0])]\n", "df_spain_tweets[\"language\"]=[\"http://id.loc.gov/vocabulary/iso639-2/spa\" for x in range(df_spain_tweets.shape[0])]\n", "df_spain_tweets[\"id\"]= [f\"twes{x}\" for x in range(df_spain_tweets.shape[0])]\n", "df_spain_tweets[\"word_count\"]= [len(str(text).split()) for text in df_spain_tweets[\"content\"]]\n", "df_spain_tweets[\"content\"]= [str(x).replace(\"\\\"\", \"\\'\").replace(\"“\", \"\\'\") for x in df_spain_tweets[\"content\"]]\n", "\n", "### ----------- ###\n", "\n", "df_spain_facebook_ads.drop(['id_anuncio'], axis=1, inplace=True)\n", "df_spain_facebook_ads.drop(['id_nombre_archivo'], axis=1, inplace=True)\n", "df_spain_facebook_ads.drop(['elecciones'], axis=1, inplace=True)\n", "df_spain_facebook_ads.drop(['Identificador_Fb'], axis=1, inplace=True)\n", "df_spain_facebook_ads.drop(['Fecha cierre'], axis=1, inplace=True)\n", "df_spain_facebook_ads.drop(['Texto de las Fechas'], axis=1, inplace=True)\n", "df_spain_facebook_ads.drop(['Imagen'], axis=1, inplace=True)\n", "df_spain_facebook_ads.drop(['Video'], axis=1, inplace=True)\n", "df_spain_facebook_ads.drop(['Carrusel'], axis=1, inplace=True)\n", "df_spain_facebook_ads.drop(['Dinero'], axis=1, inplace=True)\n", "df_spain_facebook_ads.drop(['id_contenido_anuncio'], axis=1, inplace=True)\n", "df_spain_facebook_ads.rename(columns = {'Fecha lanzamiento':'date'}, inplace = True) \n", "df_spain_facebook_ads.rename(columns = {'Texto del Anuncio':'content'}, inplace = True) \n", "df_spain_facebook_ads.rename(columns = {'Impresiones':'views'}, inplace = True) \n", "df_spain_facebook_ads.rename(columns = {'Partido':'account'}, inplace = True)\n", "df_spain_facebook_ads[\"account\"]= [x.replace(\" \",\"\") for x in df_spain_facebook_ads[\"account\"]]\n", "df_spain_facebook_ads[\"date\"]= [str(datetime.strptime(f\"{row[:-2]}2019\", '%d/%m/%Y').isoformat()) for row in df_spain_facebook_ads[\"date\"]]\n", "df_spain_facebook_ads[\"mentions\"]= [re.findall(pattern_facebook_mentions, str(text), re.IGNORECASE) for text in df_spain_facebook_ads[\"content\"]]\n", "df_spain_facebook_ads[\"hashtags\"]= [re.findall(pattern_hashtag, str(text), re.IGNORECASE) for text in df_spain_facebook_ads[\"content\"]]\n", "df_spain_facebook_ads[\"links\"]= [re.findall(pattern_links, str(text), re.IGNORECASE) for text in df_spain_facebook_ads[\"content\"]]\n", "df_spain_facebook_ads[\"agent\"]= [wikidata_agent[x.lower()] for x in df_spain_facebook_ads[\"account\"]]\n", "df_spain_facebook_ads[\"ideology\"]= [wikidata_ideology[x.lower()] for x in df_spain_facebook_ads[\"account\"]]\n", "df_spain_facebook_ads[\"media\"]=[\"Facebook\" for x in range(df_spain_facebook_ads.shape[0])]\n", "df_spain_facebook_ads[\"media_url\"]=[\"https://facebook.com/\" for x in range(df_spain_facebook_ads.shape[0])]\n", "df_spain_facebook_ads[\"source\"]=[\"https://doi.org/10.4995/Dataset/10251/146502\" for x in range(df_spain_facebook_ads.shape[0])]\n", "df_spain_facebook_ads[\"language\"]=[\"http://id.loc.gov/vocabulary/iso639-2/spa\" for x in range(df_spain_facebook_ads.shape[0])]\n", "df_spain_facebook_ads[\"id\"]= [f\"fbesads{x}\" for x in range(df_spain_facebook_ads.shape[0])]\n", "df_spain_facebook_ads[\"word_count\"]= [len(str(text).split()) for text in df_spain_facebook_ads[\"content\"]]\n", "df_spain_facebook_ads[\"content\"]= [str(x).replace(\"\\\"\", \"\\'\").replace(\"“\", \"\\'\") for x in df_spain_facebook_ads[\"content\"]]\n", "\n", "### ----------- ###\n", " \n", "#The trump dataset comes with mentions and hashtags fields\n", "df_trump_tweets.fillna(\"\", inplace=True)\n", "df_trump_tweets.rename(columns = {'retweets':'reposts'}, inplace = True) \n", "df_trump_tweets.rename(columns = {'link':'source'}, inplace = True) \n", "df_trump_tweets.rename(columns = {'favorites':'likes'}, inplace = True) \n", "df_trump_tweets[\"links\"]= [re.findall(pattern_links, str(text), re.IGNORECASE) for text in df_trump_tweets[\"content\"]]\n", "df_trump_tweets[\"account\"]=[\"realDonaldTrump\" for x in range(df_trump_tweets.shape[0])]\n", "df_trump_tweets[\"agent\"]= [wikidata_agent[x.lower()] for x in df_trump_tweets[\"account\"]]\n", "df_trump_tweets[\"ideology\"]= [wikidata_ideology[x.lower()] for x in df_trump_tweets[\"account\"]]\n", "df_trump_tweets[\"media\"]=[\"Twitter\" for x in range(df_trump_tweets.shape[0])]\n", "df_trump_tweets[\"media_url\"]=[\"https://twitter.com/\" for x in range(df_trump_tweets.shape[0])]\n", "df_trump_tweets[\"language\"]=[\"http://id.loc.gov/vocabulary/iso639-2/eng\" for x in range(df_trump_tweets.shape[0])]\n", "df_trump_tweets[\"mentions\"]= [x.replace(\"@\", \"\").split(\",\") for x in df_trump_tweets[\"mentions\"]]\n", "df_trump_tweets[\"hashtags\"]= [x.replace(\"#\", \"\").split(\",\") for x in df_trump_tweets[\"hashtags\"]]\n", "df_trump_tweets['id'] = df_trump_tweets['id'].astype(str)\n", "df_trump_tweets[\"word_count\"]= [len(str(text).split()) for text in df_trump_tweets[\"content\"]]\n", "df_trump_tweets[\"content\"]= [str(x).replace(\"\\\"\", \"\\'\").replace(\"“\", \"\\'\") for x in df_trump_tweets[\"content\"]]\n", "\n", "### ----------- ###\n", "\n", "df_biden_tweets.rename(columns = {'tweet':'content'}, inplace = True) \n", "df_biden_tweets.rename(columns = {'retweets':'reposts'}, inplace = True) \n", "df_biden_tweets.rename(columns = {'url':'source'}, inplace = True) \n", "df_biden_tweets.rename(columns = {'timestamp':'date'}, inplace = True) \n", "df_biden_tweets[\"mentions\"]= [re.findall(pattern_twitter_mentions, str(text), re.IGNORECASE) for text in df_biden_tweets[\"content\"]]\n", "df_biden_tweets[\"hashtags\"]= [re.findall(pattern_hashtag, str(text), re.IGNORECASE) for text in df_biden_tweets[\"content\"]]\n", "df_biden_tweets[\"links\"]= [re.findall(pattern_links, str(text), re.IGNORECASE) for text in df_biden_tweets[\"content\"]]\n", "df_biden_tweets[\"account\"]=[\"joebiden\" for x in range(df_biden_tweets.shape[0])]\n", "df_biden_tweets[\"agent\"]= [wikidata_agent[x.lower()] for x in df_biden_tweets[\"account\"]]\n", "df_biden_tweets[\"ideology\"]= [wikidata_ideology[x.lower()] for x in df_biden_tweets[\"account\"]]\n", "df_biden_tweets[\"date\"]= [str(datetime.strptime(f\"{str(row)}\", '%d-%m-%Y %H:%M').isoformat()) for row in df_biden_tweets[\"date\"]]\n", "df_biden_tweets[\"media\"]=[\"Twitter\" for x in range(df_biden_tweets.shape[0])]\n", "df_biden_tweets[\"media_url\"]=[\"https://twitter.com/\" for x in range(df_biden_tweets.shape[0])]\n", "df_biden_tweets[\"language\"]=[\"http://id.loc.gov/vocabulary/iso639-2/eng\" for x in range(df_biden_tweets.shape[0])]\n", "#df_biden_tweets['id'] = df_biden_tweets['id'].astype(str)\n", "#Wrong kaggle data, we have to regenerate ids\n", "df_biden_tweets[\"id\"]= [f\"jbustw{x}\" for x in range(df_biden_tweets.shape[0])]\n", "df_biden_tweets[\"word_count\"]= [len(str(text).split()) for text in df_biden_tweets[\"content\"]]\n", "df_biden_tweets[\"content\"]= [str(x).replace(\"\\\"\", \"\\'\").replace(\"“\", \"\\'\") for x in df_biden_tweets[\"content\"]]\n", "\n", "\n", "## Merge all datasets\n", "all_data= pd.concat([df_spain_tweets, df_spain_facebook_ads, df_biden_tweets, df_trump_tweets], axis=0, join='outer', ignore_index=True)\n", "all_data.fillna(\"\", inplace=True)\n", "\n", "## We detect noise in the dataset that causes errors, so we must remove \\ character \n", "all_data[\"content\"]= [str(x).replace(\"\\\\\", \"\\\\\\\\\") for x in all_data[\"content\"]]\n", "\n", "## Extract some data from the dataset to different JSON files. This facilitates mapping.\n", "extra_data= []\n", "metrics_data= []\n", "for r in range(all_data.shape[0]):\n", " for link in all_data[\"links\"][r]:\n", " if link==\"\": continue\n", " links_json= {\"media\": all_data[\"media\"][r],\n", " \"id\": all_data[\"id\"][r],\n", " \"account\": all_data[\"account\"][r],\n", " \"link\": link}\n", " extra_data.append(links_json)\n", "\n", " for hashtag in all_data[\"hashtags\"][r]:\n", " if hashtag==\"\": continue\n", " hashtags_json= {\"media\": all_data[\"media\"][r],\n", " \"id\": all_data[\"id\"][r],\n", " \"account\": all_data[\"account\"][r],\n", " \"hashtag\": hashtag}\n", " extra_data.append(hashtags_json)\n", " \n", " for mention in all_data[\"mentions\"][r]:\n", " if mention==\"\": continue\n", " mentions_json= {\"media\": all_data[\"media\"][r],\n", " \"id\": all_data[\"id\"][r],\n", " \"account\": all_data[\"account\"][r],\n", " \"mention\": mention}\n", " extra_data.append(mentions_json)\n", " \n", " #Views\n", " views= all_data[\"views\"][r]\n", " if views !=\"\":\n", " views_json= {\"media\": all_data[\"media\"][r],\n", " \"id\": all_data[\"id\"][r],\n", " \"account\": all_data[\"account\"][r],\n", " \"metric\": \"http://schema.org/ViewAction\",\n", " \"metric_name\": \"ViewAction\",\n", " \"number\": views}\n", " metrics_data.append(views_json)\n", " \n", " #Replies\n", " replies = all_data[\"replies\"][r]\n", " if replies !=\"\": \n", " replies_json= { \"media\": all_data[\"media\"][r],\n", " \"id\": all_data[\"id\"][r],\n", " \"account\": all_data[\"account\"][r],\n", " \"metric\": \"http://schema.org/ReplyAction\",\n", " \"metric_name\": \"ReplyAction\",\n", " \"number\": replies}\n", " metrics_data.append(replies_json)\n", "\n", " #Reposts\n", " reposts= all_data[\"reposts\"][r]\n", " if reposts !=\"\":\n", " reposts_json= { \"media\": all_data[\"media\"][r],\n", " \"id\": all_data[\"id\"][r],\n", " \"account\": all_data[\"account\"][r],\n", " \"metric\": \"http://schema.org/ShareAction\",\n", " \"metric_name\": \"ShareAction\",\n", " \"number\": reposts}\n", " metrics_data.append(reposts_json)\n", " \n", " #Quotes\n", " quotes= all_data[\"quotes\"][r]\n", " if quotes !=\"\":\n", " quotes_json= {\"media\": all_data[\"media\"][r],\n", " \"id\": all_data[\"id\"][r],\n", " \"account\": all_data[\"account\"][r],\n", " \"metric\": \"http://schema.org/CommentAction\",\n", " \"metric_name\": \"CommentAction\",\n", " \"number\": quotes}\n", " metrics_data.append(quotes_json)\n", " \n", " #Likes\n", " likes= all_data[\"likes\"][r]\n", " if likes !=\"\":\n", " likes_json= {\"media\": all_data[\"media\"][r],\n", " \"id\": all_data[\"id\"][r],\n", " \"account\": all_data[\"account\"][r],\n", " \"metric\": \"http://schema.org/LikeAction\",\n", " \"metric_name\": \"LikeAction\",\n", " \"number\": likes}\n", " metrics_data.append(likes_json)\n", "\n", "\n", "## Remove redundant fields that exists in JSONs\n", "all_data.drop(['mentions'], axis=1, inplace=True)\n", "all_data.drop(['hashtags'], axis=1, inplace=True)\n", "all_data.drop(['links'], axis=1, inplace=True)\n", "\n", "all_data.drop(['views'], axis=1, inplace=True)\n", "all_data.drop(['replies'], axis=1, inplace=True)\n", "all_data.drop(['reposts'], axis=1, inplace=True)\n", "all_data.drop(['quotes'], axis=1, inplace=True)\n", "all_data.drop(['likes'], axis=1, inplace=True)\n", "\n", "## Export the dataset and the JSON files\n", "with open(f\"{filename_extra_data}.json\", \"w\") as f:\n", " json.dump(extra_data, f)\n", " \n", "with open(f\"{filename_metrics_data}.json\", \"w\") as f:\n", " json.dump(metrics_data, f)\n", " \n", "all_data.to_csv(f\"{filename_all_data}.csv\", sep=',', index=False)\n", " " ] }, { "cell_type": "code", "execution_count": 32, "id": "aded5d7d", "metadata": { "ExecuteTime": { "end_time": "2024-02-12T12:00:42.915435Z", "start_time": "2024-02-12T12:00:36.282970Z" }, "code_folding": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Conversational Discourse Triples Generated\n" ] } ], "source": [ "# Generate the data mapping file to transform the above data into triples\n", "import os\n", "\n", "## Set filenames (WITHOUT extension)\n", "filename_mappings= \"mappings/mappings_conversational\"\n", "if not os.path.exists(\"mappings\"): os.mkdir(\"mappings\")\n", "\n", "## Generate mapping file according to the JSONs and dataset\n", "mapping= f\"\"\"\n", "prefixes:\n", " #Core imports\n", " rdf: \"http://www.w3.org/1999/02/22-rdf-syntax-ns#\"\n", " rdfs: \"http://www.w3.org/2000/01/rdf-schema#\"\n", " xsd: \"http://www.w3.org/2001/XMLSchema#\"\n", " xml: \"http://www.w3.org/XML/1998/namespace\"\n", " #Vocabulary imports\n", " schema: \"http://schema.org/\"\n", " terms: \"http://purl.org/dc/terms/\"\n", " dc: \"http://purl.org/dc/elements/1.1/\"\n", " dcam: \"http://purl.org/dc/dcam/\"\n", " vann: \"http://purl.org/vocab/vann/\"\n", " skos: \"http://www.w3.org/2004/02/skos/core#\"\n", " #Ontology imports\n", " owl: \"http://www.w3.org/2002/07/owl#\"\n", " foaf: \"http://xmlns.com/foaf/0.1/\"\n", " sioc: \"http://rdfs.org/sioc/ns#\"\n", " lkg: \"http://lkg.lynx-project.eu/def/\"\n", " nif: \"http://persistence.uni-leipzig.org/nlp2rdf/ontologies/nif-core#\"\n", " eli: \"http://data.europa.eu/eli/ontology#\"\n", " #Knowledge graph domain declaration\n", " podio: \"http://w3id.org/podio#\" # URL to ontoology\n", "\n", "sources:\n", " extra_json: [{filename_extra_data}.json~jsonpath, \"$.[*]\"]\n", " metrics_json: [{filename_metrics_data}.json~jsonpath, \"$.[*]\"]\n", " data: [{filename_all_data}.csv~csv ]\n", "\n", "mappings:\n", " Conversational:\n", " sources:\n", " - data\n", " s: podio:Conversational/$(media)/$(account)/$(id)\n", " po:\n", " - [a, podio:Conversational]\n", " - [terms:language, $(language)~iri]\n", " - [terms:created, $(date), xsd:dateTime]\n", " - [terms:source, $(source)~iri]\n", " - [terms:identifier, $(id), xsd:string]\n", " - [terms:publisher, $(agent)~iri]\n", " - [terms:creator, $(agent)~iri]\n", " - [sioc:has_creator, podio:UserAccount/$(media)/$(account)~iri]\n", " - [podio:content, $(content), xsd:string]\n", " - [podio:ideology, $(ideology)~iri]\n", " - [schema:wordCount, $(word_count)]\n", "\n", " conversationalObjectProperties:\n", " sources:\n", " - extra_json\n", " s: podio:Conversational/$(media)/$(account)/$(id)\n", " po:\n", " - [sioc:has_container, podio:Hashtag/$(hashtag)~iri]\n", " - [sioc:links_to, $(link), xsd:string]\n", " - [sioc:mentions, podio:UserAccount/$(media)/$(mention)~iri]\n", " \n", " Hashtag:\n", " sources:\n", " - extra_json\n", " s: podio:Hashtag/$(hashtag)\n", " po:\n", " - [a, podio:Hashtag]\n", " - [terms:identifier, $(hashtag), xsd:string]\n", "\n", " InteractionCounter:\n", " sources:\n", " - metrics_json\n", " s: podio:Conversational/$(media)/$(account)/$(id)/$(metric_name)\n", " po:\n", " - [a, schema:InteractionCounter]\n", " - [schema:interactionType, $(metric)~iri]\n", " - [schema:userInteractionCount, $(number), xsd:string]\n", " \n", " interactionStatistic:\n", " sources:\n", " - metrics_json\n", " s: podio:Conversational/$(media)/$(account)/$(id)\n", " po:\n", " - [schema:interactionStatistic, podio:Conversational/$(media)/$(account)/$(id)/$(metric_name)~iri]\n", " \n", " UserAccount:\n", " sources:\n", " - data\n", " s: podio:UserAccount/$(media)/$(account)\n", " po:\n", " - [a, sioc:UserAccount]\n", " - [sioc:account_of, $(agent)]\n", " - [foaf:accountName, $(account), xsd:string]\n", " - [foaf:accountServiceHomepage, $(media_url)]\n", " - [sioc:creator_of, podio:Conversational/$(media)/$(account)/$(id)]\n", " Agent:\n", " sources: \n", " - data\n", " s: $(agent)\n", " po:\n", " - [a, foaf:Agent]\n", " - [rdfs:isDefinedBy, $(agent)~iri]\n", " - [foaf:holdsAccount, podio:UserAccount/$(media)/$(account)~iri]\n", " \n", "\"\"\"\n", "\n", "## Save mappings file\n", "with open(f\"{filename_mappings}.yml\", \"w\") as f:\n", " f.write(mapping)\n", " \n", "## Generate the triples\n", "generate_triples(filename_mappings)\n", "\n", "print(\"Conversational Discourse Triples Generated\")" ] }, { "cell_type": "markdown", "id": "a2bfe788", "metadata": { "heading_collapsed": true }, "source": [ "### Approved Policies" ] }, { "cell_type": "markdown", "id": "91118419", "metadata": { "hidden": true }, "source": [ "Of the resources available on the web on legislative documents, the most relevant we found to demonstrate the potential of PODIO are:\n", "\n", "Description | Dataset\n", "--- | --- \n", "**European Legal Knowledge Graph** | Moreno Schneider, J., Rehm, G., Montiel-Ponsoda, E., Rodríguez-Doncel, V., Martín-Chozas, P., Navas-Loro, M., Kaltenböck, M., Revenko, A., Karampatakis, S., Sageder, C., Gracia, J., Maganza, F., Kernerman, I., Lonke, D., Lagzdins, A., Bosque Gil, J., Verhoeven, P., Gomez Diaz, E., & Boil Ballesteros, P. (2022). Lynx: A knowledge-based AI service platform for content processing, enrichment and analysis for the legal domain. In Information Systems (Vol. 106, p. 101966). Elsevier BV. https://doi.org/10.1016/j.is.2021.101966 \n", "**Publications of Arganda del Rey city council in the official gazette of the state and of the community in the period 1985-2023**| https://datos.gob.es/es/catalogo/l01280148-publicaciones-boe-2023\n", "\n", "On the one hand, to reuse the *European Legal Knowledge Graph* resource it is not necessary to download anything, just use federated SPARQL queries to access its data. This is explored in more detail in the *Querying the graph* section. Anyway, for more information check the [documentation](https://www.w3.org/TR/sparql11-federated-query/).\n", "\n", "On the other hand, to exploit the open data of Arganda del Rey city council, we will follow the steps below. It is mandatory to download the package [PyMuPDF](https://pypi.org/project/PyMuPDF/) to read the content of the legislation in pdf format. " ] }, { "cell_type": "code", "execution_count": null, "id": "a8a824cf", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T16:57:46.910250Z", "start_time": "2024-02-06T16:57:46.234081Z" }, "hidden": true }, "outputs": [], "source": [ "# Dataset downloading\n", "import requests\n", "import os \n", "\n", "## Generate folders where data will be stored\n", "if not os.path.exists(\"data\"): os.mkdir(\"data\")\n", "if not os.path.exists(\"data/aux\"): os.mkdir(\"data/aux\")\n", "\n", "## Downloading and storage of the dataset\n", "response = requests.get(\"https://datosabiertos.ayto-arganda.es/dataset/e519f1ba-8dfd-41b0-bda0-5b6660dbdda7/resource/99282a1a-8eaf-41dd-8cf4-cef6f930b0a3/download/publicaciones1985_2023.csv\")\n", "open(\"data/arganda.csv\", \"w\").write(response.content.decode('utf-8-sig'))\n" ] }, { "cell_type": "code", "execution_count": null, "id": "788e702f", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T16:58:40.092250Z", "start_time": "2024-02-06T16:57:46.915631Z" }, "code_folding": [ 21, 71 ], "hidden": true }, "outputs": [], "source": [ "# Dataset loading and enriching\n", "import pandas as pd\n", "from datetime import datetime\n", "import fitz \n", "import numpy as np\n", "import os\n", "import requests\n", "import xml.etree.ElementTree as ET\n", "\n", "## Set filenames (WITHOUT extension)\n", "filename_legislations= \"data/legislation\"\n", "\n", "## Limit to avoid overloading the graph database due to excessive volume of data sets.\n", "limit=4000 #If you do not want limit set as None\n", "\n", "## Dataset loading\n", "df_arganda_legislation= pd.read_csv(\"data/arganda.csv\", sep=';', on_bad_lines='skip')[:limit]\n", "\n", "## Extracting the content of the pdf links\n", "content= []\n", "\n", "for index, link in enumerate(df_arganda_legislation[\"Hipervinculo\"]):\n", " filename_aux= f\"data/aux/{link.split('/')[-1].split('.pdf')[0]}.pdf\"\n", " \n", " if not os.path.isfile(filename_aux):\n", " #Download the file\n", " headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/109.0.0.0 Safari/537.36'}\n", " try:\n", " response = requests.get(link, headers=headers)\n", " if response.status_code == 200:\n", " open(filename_aux, \"wb\").write(response.content)\n", " else:\n", " open(filename_aux, \"w\").write(\"\")\n", " except:\n", " open(filename_aux, \"w\").write(\"\")\n", " try: \n", " with fitz.open(filename_aux) as doc:\n", " global_text = []\n", " doc_content= \"\"\n", " for pagenumber, page in enumerate(doc):\n", " doc_content+= page.get_text()\n", " content.append(doc_content.replace(\"\\\"\", \"\\'\")) #Is important to remove because otherwhise will generate malformed csv\n", " except:\n", " content.append(\"\")\n", "\n", "## Manual entity linking\n", "publishers= {\"BOE\": \"http://www.wikidata.org/entity/Q5659724\", \"BOC\": \"http://www.wikidata.org/entity/Q578788\"}\n", "audiences= {\"BOE\": \"http://www.wikidata.org/entity/Q29\", \"BOC\": \"http://www.wikidata.org/entity/Q5756\"}\n", "\n", "## Dataset cleaning and enriching\n", "df_arganda_legislation[\"content\"]= content\n", "df_arganda_legislation.rename(columns = {'Hipervinculo':'source'}, inplace = True) \n", "df_arganda_legislation.rename(columns = {'Fecha':'date'}, inplace = True) \n", "df_arganda_legislation.rename(columns = {'Materia':'topic'}, inplace = True) \n", "df_arganda_legislation.rename(columns = {'Descripcion':'description'}, inplace = True) \n", "df_arganda_legislation.rename(columns = {'Año':'year'}, inplace = True) \n", "df_arganda_legislation[\"publisher\"] = [publishers[x] for x in df_arganda_legislation[\"Boletin\"]]\n", "df_arganda_legislation[\"audience\"]= [audiences[x] for x in df_arganda_legislation[\"Boletin\"]]\n", "df_arganda_legislation[\"date\"]= [str(datetime.strptime(row, \"%Y-%m-%d\").isoformat()) for row in df_arganda_legislation[\"date\"]]\n", "df_arganda_legislation[\"language\"]=[\"http://id.loc.gov/vocabulary/iso639-2/spa\" for x in range(df_arganda_legislation.shape[0])]\n", "df_arganda_legislation[\"creator\"]=[\"http://www.wikidata.org/entity/Q60052813\" for x in range(df_arganda_legislation.shape[0])]\n", "df_arganda_legislation[\"jurisdiction\"]=[\"ES-MA\" for x in range(df_arganda_legislation.shape[0])]\n", "df_arganda_legislation[\"title\"]=[\" \" for x in range(df_arganda_legislation.shape[0])]\n", "df_arganda_legislation[\"word_count\"]= [len(x.split()) for x in df_arganda_legislation[\"content\"]]\n", "\n", "## Extracting and generating legislative document identifiers\n", "parents_links= []\n", "parent_ids= []\n", "parent_pdfs= []\n", "ids= []\n", "\n", "for x in range(df_arganda_legislation.shape[0]):\n", "\n", " if df_arganda_legislation[\"Boletin\"][x]==\"BOE\":\n", " link_pdf= f\"https://www.boe.es/boe/dias/{df_arganda_legislation['date'][x].replace('-','/')}/pdfs/BOE-S-{df_arganda_legislation['date'][x].split('-')[0]}-{df_arganda_legislation['Numero Boletin'][x]}.pdf\"\n", " parent_pdfs.append(link_pdf)\n", " \n", " parent_id= f\"BOE-S-{df_arganda_legislation['year'][x]}-{df_arganda_legislation['Numero Boletin'][x]}\"\n", " parent_ids.append(parent_id)\n", "\n", " link_xml= f\"https://www.boe.es/diario_boe/xml.php?id={parent_id}\"\n", " xmlstring= requests.get(link_xml).content.decode(\"utf-8\")\n", " tree = ET.ElementTree(ET.fromstring(xmlstring))\n", " \n", " parent_map = {c: p for p in tree.iter() for c in p}\n", " found= False\n", " for idx, c in enumerate(tree.findall(\".//titulo\")):\n", " if c.text == df_arganda_legislation[\"description\"][x]:\n", " found= True\n", " break\n", " if found: \n", " identifier= parent_map[c].attrib['id']\n", " else:\n", " e= 1\n", " while True:\n", " _id= f\"{parent_id}-{e}\"\n", " if _id not in ids:\n", " identifier= _id\n", " break\n", " else:\n", " e+= 1\n", " ids.append(identifier)\n", "\n", " link_id= f\"https://www.boe.es/diario_boe/txt.php?id={identifier}\"\n", " parents_links.append(link_id)\n", " \n", " elif df_arganda_legislation[\"Boletin\"][x]==\"BOC\":\n", " \n", " link_pdf= f\"https://www.bocm.es/boletin/CM_Boletin_BOCM/{df_arganda_legislation['date'][x].replace('-','/')}/{str(df_arganda_legislation['Numero Boletin'][x]).zfill(3)}00.pdf\"\n", " parent_pdfs.append(link_pdf)\n", " \n", " link_id= f\"https://www.bocm.es/boletin-completo/bocm-{df_arganda_legislation['date'][x].replace('-','')}/{df_arganda_legislation['Numero Boletin'][x]}/\"\n", " parents_links.append(link_id)\n", " parent_id= f\"BOCM-{df_arganda_legislation['date'][x].replace('-','')}-{df_arganda_legislation['Numero Boletin'][x]}\"\n", " parent_ids.append(parent_id)\n", " \n", " # We generate child ids because they are not defined by the CAM\n", " e= 1\n", " while True:\n", " child_id = f\"{parent_id}-{e}\"\n", " if child_id not in ids:\n", " ids.append(child_id)\n", " break\n", " else:\n", " e +=1\n", "\n", "df_arganda_legislation[\"id\"]= ids\n", "df_arganda_legislation[\"parent_id\"]= parent_ids\n", "df_arganda_legislation[\"parent_source\"]= parents_links\n", "\n", "## Remove unused columns\n", "df_arganda_legislation.drop(['Numero Boletin'], axis=1, inplace=True)\n", "df_arganda_legislation.drop(['Pagina'], axis=1, inplace=True)\n", "df_arganda_legislation.drop(['Boletin'], axis=1, inplace=True)\n", "df_arganda_legislation.drop(['year'], axis=1, inplace=True)\n", "\n", "## Export the data to csv\n", "df_arganda_legislation.to_csv(f\"{filename_legislations}.csv\", sep=',', index=False)" ] }, { "cell_type": "code", "execution_count": null, "id": "427e5506", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T17:03:18.507522Z", "start_time": "2024-02-06T16:58:40.093776Z" }, "code_folding": [ 9, 32, 35 ], "hidden": true }, "outputs": [], "source": [ "# Generate the data mapping file to transform the above data into triples\n", "import os\n", "\n", "## Set filenames (WITHOUT extension)\n", "filename_mappings= \"mappings/mappings_legislation\"\n", "if not os.path.exists(\"mappings\"): os.mkdir(\"mappings\")\n", "\n", "## Generate mapping file according to the previous dataset\n", "mapping= f\"\"\"\n", "prefixes:\n", " #Core imports\n", " rdf: \"http://www.w3.org/1999/02/22-rdf-syntax-ns#\"\n", " rdfs: \"http://www.w3.org/2000/01/rdf-schema#\"\n", " xsd: \"http://www.w3.org/2001/XMLSchema#\"\n", " xml: \"http://www.w3.org/XML/1998/namespace\"\n", " #Vocabulary imports\n", " schema: \"http://schema.org/\"\n", " terms: \"http://purl.org/dc/terms/\"\n", " dc: \"http://purl.org/dc/elements/1.1/\"\n", " dcam: \"http://purl.org/dc/dcam/\"\n", " vann: \"http://purl.org/vocab/vann/\"\n", " skos: \"http://www.w3.org/2004/02/skos/core#\"\n", " #Ontology imports\n", " owl: \"http://www.w3.org/2002/07/owl#\"\n", " foaf: \"http://xmlns.com/foaf/0.1/\"\n", " sioc: \"http://rdfs.org/sioc/ns#\"\n", " lkg: \"http://lkg.lynx-project.eu/def/\"\n", " nif: \"http://persistence.uni-leipzig.org/nlp2rdf/ontologies/nif-core#\"\n", " eli: \"http://data.europa.eu/eli/ontology#\"\n", " #Knowledge graph domain declaration\n", " podio: \"http://w3id.org/podio#\" # URL to ontoology\n", "\n", "sources:\n", " data: [{filename_legislations}.csv~csv ]\n", " \n", "mappings:\n", " ApprovedPolicy:\n", " sources:\n", " - data\n", " s: podio:ApprovedPolicy/$(id)\n", " po:\n", " - [a, podio:ApprovedPolicy]\n", " - [lkg:metadata, podio:ApprovedPolicy/$(id)/Metadata~iri]\n", " - [eli:is_part_of, podio:ApprovedPolicy/$(parent_id)~iri]\n", " - [podio:content, $(content), xsd:string]\n", " - [terms:language, $(language)~iri]\n", " - [terms:created, $(date), xsd:dateTime]\n", " - [terms:description, $(description), xsd:string]\n", " - [terms:source, $(source)~iri]\n", " - [terms:identifier, $(id), xsd:int]\n", " - [schema:wordCount, $(word_count), xsd:int]\n", " - [terms:audience, $(audience)~iri]\n", " - [terms:publisher, $(publisher)~iri]\n", " - [terms:creator, $(creator)~iri]\n", "\n", " ParentPolicy:\n", " sources:\n", " - data\n", " s: podio:ApprovedPolicy/$(parent_id)\n", " po:\n", " - [a, podio:ApprovedPolicy]\n", " - [eli:has_part, podio:ApprovedPolicy/$(id)~iri]\n", " - [terms:language, $(language)~iri]\n", " - [terms:source, $(parent_source)~iri]\n", " - [terms:identifier, $(parent_id), xsd:int]\n", " - [terms:created, $(date), xsd:dateTime]\n", " - [terms:audience, $(audience)~iri]\n", " - [terms:publisher, $(publisher)~iri]\n", " - [terms:creator, $(publisher)~iri]\n", " \n", " Metadata:\n", " sources:\n", " - data\n", " s: podio:ApprovedPolicy/$(id)/Metadata\n", " po:\n", " - [a, podio:ApprovedPolicy]\n", " - [terms:language, $(language)~iri]\n", " - [lkg:hasPDF, $(source)~iri]\n", " - [terms:source, $(parent_source)~iri]\n", " - [eli:version_date, $(date), xsd:dateTime]\n", " - [eli:id_local, $(id), xsd:string]\n", " - [lkg:summary, $(description), xsd:string]\n", " - [terms:subject, $(topic), xsd:string]\n", " - [terms:title, $(title), xsd:string]\n", " - [lkg:hasAuthority, $(publisher)~iri]\n", " - [eli:jurisdiction, $(jurisdiction), xsd:string]\n", "\n", "\"\"\"\n", "\n", "## Save mappings file\n", "with open(f\"{filename_mappings}.yml\", \"w\") as f:\n", " f.write(mapping)\n", "\n", "## Generate the triples\n", "generate_triples(filename_mappings)\n", "\n", "print(\"Approved Policies Discourse Triples Generated\")" ] }, { "cell_type": "markdown", "id": "8422c3a9", "metadata": { "heading_collapsed": true }, "source": [ "### Other Discourses" ] }, { "cell_type": "markdown", "id": "9fa08c9c", "metadata": { "hidden": true }, "source": [ "There are also other types of discourses, such as those made in Spain by the head of the state at Christmas. These speeches are expository and are broadcast on television on Christmas Eve. We found the following resource that collects the different ones: \n", "\n", "Description|Dataset\n", "---|---\n", "**Spanish head of state speeches** | Elena Álvarez-Mellado. 2020. A Corpus of Spanish Political Speeches from 1937 to 2019. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 928–932, Marseille, France. European Language Resources Association.\n", "\n", "To work with this resource it is necessary to install the [git](https://gitpython.readthedocs.io/en/stable/intro.html) package in python (or skip the step and do it manually)." ] }, { "cell_type": "code", "execution_count": null, "id": "ec1d83be", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T17:03:18.673083Z", "start_time": "2024-02-06T17:03:18.509330Z" }, "hidden": true }, "outputs": [], "source": [ "from git import Repo # pip install gitpython\n", "\n", "## Set filenames (WITHOUT extension)\n", "repo_dir= \"data/aux/discursos-de-navidad\"\n", "\n", "## Cloning repository\n", "Repo.clone_from(\"https://github.com/lirondos/discursos-de-navidad.git\", repo_dir)\n" ] }, { "cell_type": "code", "execution_count": null, "id": "025072d6", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T17:03:28.314326Z", "start_time": "2024-02-06T17:03:28.250292Z" }, "code_folding": [ 20 ], "hidden": true }, "outputs": [], "source": [ "#Dataset loading, cleaning, enriching and storage \n", "import pandas as pd\n", "import numpy as np\n", "import os\n", "\n", "## Set filenames (WITHOUT extension)\n", "repo_dir= \"data/aux/discursos-de-navidad\"\n", "filename_discursos= \"data/discursos_navidad\"\n", "\n", "## Limit to avoid overloading the graph database due to excessive volume of data sets.\n", "limit=4000 #If you do not want limit set as None else, an int\n", "\n", "## Dataset loading\n", "discursos_navidad= pd.read_csv(f\"{repo_dir}/data/metadata.csv\", sep=',', on_bad_lines='skip')[:limit]\n", "\n", "## Manual entity linking\n", "head_of_state = {\"Felipe de Borbón\": \"http://www.wikidata.org/entity/Q191045\", \n", " \"Juan Carlos de Borbón\": \"http://www.wikidata.org/entity/Q19943\", \n", " \"Francisco Franco\": \"http://www.wikidata.org/entity/Q29179\"}\n", "\n", "ideologies = { \"Felipe de Borbón\": \"\", \n", " \"Juan Carlos de Borbón\": \"\", \n", " \"Francisco Franco\": \"http://www.wikidata.org/entity/Q210890\"}\n", "\n", "\n", "## Dataset cleaning and enriching\n", "discursos_navidad.rename(columns = {'url_text':'source'}, inplace = True) \n", "discursos_navidad.rename(columns = {'head_of_state':'creator'}, inplace = True) \n", "discursos_navidad[\"ideology\"]= [ideologies[x] for x in discursos_navidad[\"creator\"]]\n", "discursos_navidad[\"creator\"]= [head_of_state[x] for x in discursos_navidad[\"creator\"]]\n", "discursos_navidad[\"target\"]= [\"http://www.wikidata.org/entity/Q29\" for x in range(discursos_navidad.shape[0])]\n", "discursos_navidad[\"language\"]=[\"http://id.loc.gov/vocabulary/iso639-2/spa\" for x in range(discursos_navidad.shape[0])]\n", "discursos_navidad[\"id\"]=[f\"{x}-spa-christmas\" for x in discursos_navidad[\"year\"]]\n", "discursos_navidad.rename(columns = {'year':'date'}, inplace = True) \n", "discursos_navidad[\"date\"]= [f\"{x}-12-24T21:00:00\" for x in discursos_navidad[\"date\"]]\n", "\n", "## Read discourse files content and add to the dataset\n", "contents= []\n", "for file_name in discursos_navidad[\"file_name\"]:\n", " with open(f\"{repo_dir}/data/speeches/{file_name}\", \"r\") as f:\n", " contents.append(f.read())\n", "discursos_navidad[\"content\"]= contents\n", "discursos_navidad[\"word_count\"]= [len(x.split()) for x in discursos_navidad[\"content\"]]\n", "discursos_navidad.drop(['file_name'], axis=1, inplace=True)\n", "\n", "## Save dataset to file\n", "discursos_navidad.to_csv(f\"{filename_discursos}.csv\", sep=',', index=False)\n" ] }, { "cell_type": "code", "execution_count": null, "id": "d5ac6f86", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T17:03:31.975300Z", "start_time": "2024-02-06T17:03:29.104828Z" }, "code_folding": [ 9 ], "hidden": true }, "outputs": [], "source": [ "# Generate the data mapping file to transform the above data into triples\n", "import os\n", "\n", "## Set filenames (WITHOUT extension)\n", "filename_mappings= \"mappings/mappings_discursos_navidad\"\n", "if not os.path.exists(\"mappings\"): os.mkdir(\"mappings\")\n", "\n", "## Generate mapping file according to the JSONs and dataset\n", "mapping= f\"\"\"\n", "prefixes:\n", " #Core imports\n", " rdf: \"http://www.w3.org/1999/02/22-rdf-syntax-ns#\"\n", " rdfs: \"http://www.w3.org/2000/01/rdf-schema#\"\n", " xsd: \"http://www.w3.org/2001/XMLSchema#\"\n", " xml: \"http://www.w3.org/XML/1998/namespace\"\n", " #Vocabulary imports\n", " schema: \"http://schema.org/\"\n", " terms: \"http://purl.org/dc/terms/\"\n", " dc: \"http://purl.org/dc/elements/1.1/\"\n", " dcam: \"http://purl.org/dc/dcam/\"\n", " vann: \"http://purl.org/vocab/vann/\"\n", " skos: \"http://www.w3.org/2004/02/skos/core#\"\n", " #Ontology imports\n", " owl: \"http://www.w3.org/2002/07/owl#\"\n", " foaf: \"http://xmlns.com/foaf/0.1/\"\n", " sioc: \"http://rdfs.org/sioc/ns#\"\n", " lkg: \"http://lkg.lynx-project.eu/def/\"\n", " nif: \"http://persistence.uni-leipzig.org/nlp2rdf/ontologies/nif-core#\"\n", " eli: \"http://data.europa.eu/eli/ontology#\"\n", " #Knowledge graph domain declaration\n", " podio: \"http://w3id.org/podio#\" # URL to ontoology\n", "\n", "sources:\n", " data: [{filename_discursos}.csv~csv ]\n", "\n", "mappings:\n", " Expository:\n", " sources:\n", " - data\n", " s: podio:Expository/$(id)\n", " po:\n", " - [a, podio:Expository]\n", " - [terms:identifier, $(id), xsd:int]\n", " - [podio:content, $(content), xsd:string]\n", " - [terms:language, $(language)~iri]\n", " - [terms:created, $(date), xsd:dateTime]\n", " - [terms:source, $(source)~iri]\n", " - [schema:wordCount, $(word_count), xsd:int]\n", " - [podio:hasTarget, $(target)~iri]\n", " - [podio:ideology, $(ideology)~iri]\n", " - [terms:creator, $(creator)~iri]\n", "\n", "\"\"\"\n", "\n", "## Save mappings file\n", "with open(f\"{filename_mappings}.yml\", \"w\") as f:\n", " f.write(mapping)\n", "\n", "## Generate the triples\n", "\n", "generate_triples(filename_mappings)\n", "\n", "print(\"Expository Discourse Triples Generated\")" ] }, { "cell_type": "markdown", "id": "449d388a", "metadata": { "heading_collapsed": true }, "source": [ "### Additional Triples" ] }, { "cell_type": "markdown", "id": "fa22b803", "metadata": { "hidden": true }, "source": [ "Aquí generamos tripletas transversales para el correcto funcionamiento del grafo. Entre las tripletas que creamos son las de definir algunos agentes como partidos políticos, " ] }, { "cell_type": "code", "execution_count": null, "id": "ed67a59b", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T17:04:10.606120Z", "start_time": "2024-02-06T17:04:10.601820Z" }, "hidden": true }, "outputs": [], "source": [ "# Generate the extra triples \n", "import os\n", "\n", "## Set filenames (WITHOUT extension)\n", "filename_extra= \"mappings/extra_triples\"\n", "if not os.path.exists(\"mappings\"): os.mkdir(\"mappings\")\n", "\n", " \n", "wikidata_id= { \n", " \"http://www.wikidata.org/entity/Q623740\": \"Q623740\",\n", " \"http://www.wikidata.org/entity/Q1393123\": \"Q1393123\",\n", " \"http://www.wikidata.org/entity/Q138198\": \"Q138198\",\n", " \"http://www.wikidata.org/entity/Q185088\": \"Q185088\",\n", " \"http://www.wikidata.org/entity/Q16059622\": \"Q16059622\",\n", " \"http://www.wikidata.org/entity/Q15630787\": \"Q15630787\",\n", " \"http://www.wikidata.org/entity/Q29552\": \"Q29552\",\n", " \"http://www.wikidata.org/entity/Q29468\": \"Q29468\",\n", " \"http://www.wikidata.org/entity/Q22686\": \"Q22686\",\n", " \"http://www.wikidata.org/entity/Q6279\": \"Q6279\",\n", " \"http://www.wikidata.org/entity/Q191045\": \"Q191045\",\n", " \"http://www.wikidata.org/entity/Q19943\": \"Q19943\",\n", " \"http://www.wikidata.org/entity/Q29179\": \"Q29179\",\n", " \"http://www.wikidata.org/entity/Q60052813\": \"Q60052813\"\n", " \n", "}\n", "\n", "\n", "trip= \"\"\n", "for key, value in wikidata_id.items():\n", " trip += f'<{key}> \"{value}\".\\n'\n", "\n", "\n", "with open(f\"{filename_extra}.nt\", \"w\") as f:\n", " f.write(trip)\n", "\n", "print(\"Extra triples generated\")\n" ] }, { "cell_type": "markdown", "id": "4846f258", "metadata": { "heading_collapsed": true }, "source": [ "### Summary" ] }, { "cell_type": "markdown", "id": "51a8ba40", "metadata": { "hidden": true }, "source": [ "In this section we downloaded different datasets available on the internet on political discourse from different countries. We cleaned, enriched, merged and mapped them to the ontology to generate the triplets. We set a limit of the first 4000 entries for each dataset in order to make the database solve queries faster. However, this notebook can be used to load more datasets without any limit. The triples that we generated, and to which we are going to make queries are:\n", "\n", "Categories | Triples\n", "--- | ---\n", "Party Manifestos and Political Proposals | 19.390\n", "Social Media Posts | 446.346\n", "Approved Policies | 127.838\n", "Other Discoueses | 743\n", "Additional triples | 14\n", "**Total** | **549.321**" ] }, { "cell_type": "markdown", "id": "9a34256c", "metadata": { "heading_collapsed": true }, "source": [ "## Querying the graph" ] }, { "cell_type": "markdown", "id": "4cbc1f84", "metadata": { "hidden": true }, "source": [ "To execute the queries we used the python package [SPARQLWrapper](https://pypi.org/project/SPARQLWrapper/). The endpoint we use is the one associated to https://w3id.org/podio/sparql, although you are free to use another one and replicate or expand the previous processes. " ] }, { "cell_type": "code", "execution_count": null, "id": "cc939de1", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T14:05:45.176985Z", "start_time": "2024-02-06T14:05:45.172872Z" }, "code_folding": [], "hidden": true, "hide_input": false, "scrolled": true }, "outputs": [], "source": [ "#Default endpoint configuration to run SPARQL queries\n", "from SPARQLWrapper import SPARQLWrapper, JSON, CSV\n", "import pandas as pd\n", "from io import StringIO\n", "from IPython.display import display, HTML\n", "\n", "sparql = SPARQLWrapper(\"https://graphdb.linkeddata.es/repositories/podio\")\n", "sparql.setReturnFormat(CSV)\n", "\n", "\n", "\n", "def run_query(query):\n", " sparql.setQuery(query)\n", " try:\n", " results = sparql.queryAndConvert()\n", " decode_results= results.decode(encoding='utf-8', errors='strict')\n", " df = pd.read_csv(StringIO(decode_results), sep=\",\")\n", " display(HTML(df.to_html()))\n", " except Exception as e:\n", " print(e)" ] }, { "cell_type": "markdown", "id": "d30b3600", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### CQ1: What are the names of all political parties, when were they created and what is their ideology?" ] }, { "cell_type": "code", "execution_count": null, "id": "250dc2b3", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T16:06:47.306125Z", "start_time": "2024-02-06T16:06:44.547887Z" }, "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select ?name ?creationDate ?ideologyLabel where { \n", "\n", " select ?s (SAMPLE(?creation) as ?creationDate) (SAMPLE(?ideologyLabel) as ?ideologyLabel) (SAMPLE(?name) as ?name)\n", " where { \n", "\n", " ?s a foaf:Agent;\n", " terms:identifier ?id.\n", "\n", " BIND(IRI(CONCAT(\"http://www.wikidata.org/entity/\", str(?id))) AS ?wikidataIri) .\n", "\n", " # Query Wikidata using federation\n", " SERVICE {\n", " ?wikidataIri rdfs:label ?name;\n", " wdt:P31/wdt:P279* wd:Q7278;\n", " wdt:P571 ?creation;\n", " wdt:P1387 ?ideology.\n", " ?ideology rdfs:label ?ideologyLabel.\n", " FILTER(LANGMATCHES(LANG(?name), \"en\")).\n", " FILTER(LANGMATCHES(LANG(?ideologyLabel), \"en\")).\n", " SERVICE wikibase:label { bd:serviceParam wikibase:language \"en\". }\n", " }\n", " } group by ?s\n", "\n", "}\n", "\"\"\"\n", "\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "5058fe5f", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### CQ2: Which social media accounts does the PP have?" ] }, { "cell_type": "code", "execution_count": null, "id": "53d1d027", "metadata": { "ExecuteTime": { "end_time": "2024-02-05T16:06:29.421807Z", "start_time": "2024-02-05T16:06:29.388101Z" }, "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select ?socialMediaUserName ?socialMedia where { \n", " foaf:holdsAccount ?accounts .\n", " ?accounts foaf:accountServiceHomepage ?socialMedia;\n", " foaf:accountName ?socialMediaUserName.\n", "} \n", "\"\"\"\n", "\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "025c2929", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### CQ3: How many posts have political parties published on each of their social media accounts?" ] }, { "cell_type": "code", "execution_count": null, "id": "7a267a58", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T16:10:08.850489Z", "start_time": "2024-02-06T16:10:03.989746Z" }, "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "\n", "select (?name as ?PoliticalParty) ?socialMedia (?accname as ?accountName) ?numberOfpost where { \n", "\n", " select ?socialMedia ?accname\n", " (SAMPLE(?name) AS ?name)\n", " (COUNT(DISTINCT(?discourse)) AS ?numberOfpost) \n", " where { \n", " ?discourse a podio:Discourse;\n", " sioc:has_creator ?account.\n", " ?s a foaf:Agent;\n", " terms:identifier ?ids;\n", " foaf:holdsAccount ?account .\n", " ?account foaf:accountServiceHomepage ?socialMedia;\n", " foaf:accountName ?accname.\n", " BIND(IRI(CONCAT(\"http://www.wikidata.org/entity/\", str(?ids))) AS ?wikidataIri) .\n", "\n", " # Query Wikidata using federation\n", " SERVICE {\n", " ?wikidataIri rdfs:label ?name;\n", " wdt:P31/wdt:P279* wd:Q7278.\n", " FILTER(LANGMATCHES(LANG(?name), \"en\")).\n", " SERVICE wikibase:label { bd:serviceParam wikibase:language \"en\". }\n", " }\n", " } group by ?socialMedia ?accname\n", "}\n", "\"\"\"\n", "\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "75c9eea2", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### CQ4: Which account and on which social media network is the most mentioned by each politician and political party?" ] }, { "cell_type": "code", "execution_count": null, "id": "86a96a91", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T14:07:14.006517Z", "start_time": "2024-02-06T14:07:12.214027Z" }, "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "\n", "SELECT (SAMPLE(?name) as ?agentName) (SAMPLE(?socialMedia) as ?socialMedia) (SAMPLE(?mentioned_account) as ?maxMentionedAccount) (MAX(?count_mentions) as ?numberOfTimesMentioned) WHERE{\n", " \n", " SELECT DISTINCT ?pparty ?name ?socialMedia ?mentioned_account (COUNT (?tweet) as ?count_mentions)\n", " WHERE {\n", " ?tweet a podio:Discourse ;\n", " sioc:mentions ?mentioned_account ;\n", " podio:content ?tweet_text ;\n", " sioc:has_creator ?account .\n", " ?pparty foaf:holdsAccount ?account;\n", " terms:identifier ?wikiId.\n", " ?account foaf:accountServiceHomepage ?socialMedia.\n", "\n", " BIND(IRI(CONCAT(\"http://www.wikidata.org/entity/\", str(?wikiId))) AS ?wikidataIri) .\n", "\n", " # Query Wikidata using federation\n", " SERVICE {\n", " ?wikidataIri rdfs:label ?name.\n", " FILTER(LANGMATCHES(LANG(?name), \"en\")).\n", " SERVICE wikibase:label { bd:serviceParam wikibase:language \"en\". }\n", " }\n", " } GROUP BY ?pparty ?mentioned_account ?name ?socialMedia\n", " \n", "} group by ?pparty \n", "ORDER BY DESC(?mentions)\n", "\"\"\"\n", "\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "7d50426b", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T15:03:05.467876Z", "start_time": "2024-02-06T15:03:05.464693Z" }, "heading_collapsed": true, "hidden": true }, "source": [ "### CQ5: What were the top 10 hashtags used in political speech during 2020?" ] }, { "cell_type": "code", "execution_count": null, "id": "36729a4b", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T15:02:34.584683Z", "start_time": "2024-02-06T15:02:34.489026Z" }, "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "\n", "\n", "Select ?hashtagName (MAX(?count) as ?usedTimes) where{\n", " select ?hashtagName (count(distinct ?s) as ?count) where {\n", " ?s a podio:Discourse;\n", " podio:content ?text;\n", " terms:creator ?authAcc;\n", " sioc:has_container ?container;\n", " terms:created ?date .\n", " ?container a podio:Hashtag;\n", " terms:identifier ?hashtagName.\n", "\n", " \n", " FILTER(year(?date) = 2020)\n", " } GROUP BY ?hashtagName \n", "\n", "} group by ?authAcc ?hashtagName\n", "Order BY desc (?usedTimes) LIMIT 10\n", "\n", "\"\"\"\n", "\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "3212419c", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### CQ6: Which political party has generated the most speeches?" ] }, { "cell_type": "code", "execution_count": null, "id": "7ccf644f", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T09:07:00.394957Z", "start_time": "2024-02-06T09:06:58.301208Z" }, "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select (?name as ?PoliticalParty) ?numberOfDiscourses where { \n", "\n", " select ?s\n", " (SAMPLE(?name) AS ?name)\n", " (COUNT(DISTINCT(?discourse)) AS ?numberOfDiscourses) \n", " where { \n", " ?discourse a podio:Discourse;\n", " terms:creator ?s.\n", " ?s a foaf:Agent;\n", " terms:identifier ?ids.\n", " \n", " BIND(IRI(CONCAT(\"http://www.wikidata.org/entity/\", str(?ids))) AS ?wikidataIri) .\n", "\n", " # Query Wikidata using federation\n", " SERVICE {\n", " ?wikidataIri rdfs:label ?name;\n", " wdt:P31/wdt:P279* wd:Q7278.\n", " FILTER(LANGMATCHES(LANG(?name), \"en\")).\n", " SERVICE wikibase:label { bd:serviceParam wikibase:language \"en\". }\n", " }\n", " } group by ?s\n", "}ORDER BY DESC(?numberOfDiscourses)\n", "LIMIT 1\n", "\"\"\"\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "59605058", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### CQ7: How many references to the LGTBI community have been made in each year's political speeches by the different political agents?" ] }, { "cell_type": "code", "execution_count": null, "id": "e5442aab", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T14:32:10.374675Z", "start_time": "2024-02-06T14:32:06.275746Z" }, "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select (SAMPLE(?name) as ?name) ?timeslice (count(distinct ?s) as ?count) where {\n", " ?s a podio:Discourse;\n", " podio:content ?text;\n", " terms:creator ?auth;\n", " terms:created ?date .\n", " BIND(year(?date) as ?timeslice) .\n", " filter contains(lcase(str(?text)),\"lgtbi\")\n", " \n", " ?auth terms:identifier ?ids.\n", " BIND(IRI(CONCAT(\"http://www.wikidata.org/entity/\", str(?ids))) AS ?wikidataIri) .\n", "\n", " SERVICE {\n", " ?wikidataIri rdfs:label ?name.\n", " FILTER(LANGMATCHES(LANG(?name), \"en\")).\n", " SERVICE wikibase:label { bd:serviceParam wikibase:language \"en\". }\n", " }\n", " \n", " } GROUP BY ?timeslice ?auth\n", "ORDER BY DESC (?count)\n", "\n", "\"\"\"\n", "\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "44686cf8", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### CQ8: What were the five most shared speeches?" ] }, { "cell_type": "code", "execution_count": null, "id": "bd5155ad", "metadata": { "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select ?text (?int as ?numberOfTimeShared) where { \n", " ?s a podio:Discourse;\n", " schema:interactionStatistic ?stats;\n", " terms:creator ?auth;\n", " podio:content ?text.\n", " \n", " ?stats schema:interactionType schema:ShareAction;\n", " schema:userInteractionCount ?number.\n", "\n", " BIND( abs(xsd:float(?number)) as ?int)\n", "\n", "\n", "} \n", "ORDER BY DESC (?int)\n", "LIMIT 5\n", "\"\"\"\n", "\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "f2ef6523", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### CQ9:What are the ten authorities that have approved the most legislations?" ] }, { "cell_type": "code", "execution_count": null, "id": "fabcbff8", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T11:59:57.197182Z", "start_time": "2024-02-06T11:59:41.028911Z" }, "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "\n", "SELECT ?jurisdiction (?auth as ?authority) (MAX(?numberOfLegislations) AS ?numberOfLegislations)\n", "WHERE {\n", " SELECT (?juris as ?jurisdiction) ?auth (COUNT(DISTINCT(?id)) AS ?numberOfLegislations)\n", " WHERE {\n", " {\n", " ?s a podio:ApprovedPolicy ;\n", " podio:content ?s_text ;\n", " lkg:metadata ?metadata .\n", " ?metadata eli:jurisdiction ?juris ;\n", " eli:version_date ?date ;\n", " eli:id_local ?id ;\n", " lkg:hasAuthority ?auth ;\n", " terms:source ?source .\n", " \n", " }\n", " UNION{\n", " SERVICE {\n", " ?s a lkg:Legislation ;\n", " nif:isString ?s_text ;\n", " lkg:metadata ?metadata .\n", " ?metadata eli:jurisdiction ?juris ;\n", " eli:version_date ?date ;\n", " eli:id_local ?id ;\n", " lkg:hasAuthority ?auth ;\n", " terms:source ?source .\n", " }\n", " }\n", " BIND(year(?date) as ?year)\n", " } group by ?juris ?auth\n", " \n", "} group by ?jurisdiction ?auth\n", "ORDER BY DESC(?numberOfLegislations) Limit 10\n", "\n", "\"\"\"\n", "\n", "run_query(query)\n" ] }, { "cell_type": "markdown", "id": "87c0d99d", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### CQ10: How much legislations are available for each jurisdiction and year?" ] }, { "cell_type": "code", "execution_count": null, "id": "9db23272", "metadata": { "ExecuteTime": { "end_time": "2024-02-05T10:15:05.049922Z", "start_time": "2024-02-05T10:14:48.582259Z" }, "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "SELECT (?juris as ?jurisdiction) ?year (COUNT(DISTINCT(?id)) AS ?numberOfLegislations)\n", "WHERE {\n", " {\n", " ?s a lkg:Legislation ;\n", " nif:isString ?s_text ;\n", " lkg:metadata ?metadata .\n", " ?metadata eli:jurisdiction ?juris ;\n", " eli:version_date ?date ;\n", " eli:id_local ?id ;\n", " terms:source ?source .\n", " }\n", " UNION{\n", " SERVICE {\n", " ?s a lkg:Legislation ;\n", " nif:isString ?s_text ;\n", " lkg:metadata ?metadata .\n", " ?metadata eli:jurisdiction ?juris ;\n", " eli:version_date ?date ;\n", " eli:id_local ?id ;\n", " terms:source ?source .\n", " }\n", " }\n", " BIND(year(?date) as ?year)\n", " \n", "} group by ?juris ?year\n", "\n", "\"\"\"\n", "\n", "run_query(query)\n", "\n" ] }, { "cell_type": "markdown", "id": "903e4f1f", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### CQ11: What is the year in which more legislations were approved by each jurisdiction?" ] }, { "cell_type": "code", "execution_count": null, "id": "e294725d", "metadata": { "ExecuteTime": { "end_time": "2023-12-21T11:36:05.822275Z", "start_time": "2023-12-21T11:35:50.082728Z" }, "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "SELECT ?jurisdiction (SAMPLE(?year) as ?year) (MAX(?numberOfLegislations) AS ?numberOfLegislations)\n", "WHERE {\n", " SELECT (?juris as ?jurisdiction) ?year (COUNT(DISTINCT(?id)) AS ?numberOfLegislations)\n", " WHERE {\n", " {\n", " ?s a lkg:Legislation ;\n", " nif:isString ?s_text ;\n", " lkg:metadata ?metadata .\n", " ?metadata eli:jurisdiction ?juris ;\n", " eli:version_date ?date ;\n", " eli:id_local ?id ;\n", " terms:source ?source .\n", " }\n", " UNION{\n", " SERVICE {\n", " ?s a lkg:Legislation ;\n", " nif:isString ?s_text ;\n", " lkg:metadata ?metadata .\n", " ?metadata eli:jurisdiction ?juris ;\n", " eli:version_date ?date ;\n", " eli:id_local ?id ;\n", " terms:source ?source .\n", " }\n", " }\n", " BIND(year(?date) as ?year)\n", "\n", " } group by ?juris ?year\n", "} group by ?jurisdiction\n", "\n", "\"\"\"\n", "\n", "run_query(query)\n" ] }, { "cell_type": "markdown", "id": "e65f6c41", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### CQ12: What has been the latest legislation approved by each jurisdiction?" ] }, { "cell_type": "code", "execution_count": null, "id": "b9b2b928", "metadata": { "ExecuteTime": { "end_time": "2024-02-05T10:14:12.998280Z", "start_time": "2024-02-05T10:13:53.841761Z" }, "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "\n", "\n", "SELECT (?juris as ?jurisdiction) (MAX(?date) AS ?date) (SAMPLE(?id) AS ?id) (SAMPLE(?source) AS ?source) (SAMPLE(?s_text) AS ?content) \n", "WHERE {\n", " {\n", " ?s a lkg:Legislation ;\n", " nif:isString ?s_text ;\n", " lkg:metadata ?metadata .\n", " ?metadata eli:jurisdiction ?juris ;\n", " eli:version_date ?date ;\n", " eli:id_local ?id ;\n", " terms:source ?source .\n", " }\n", " UNION{\n", " SERVICE {\n", " ?s a lkg:Legislation ;\n", " nif:isString ?s_text ;\n", " lkg:metadata ?metadata .\n", " ?metadata eli:jurisdiction ?juris ;\n", " eli:version_date ?date ;\n", " eli:id_local ?id ;\n", " terms:source ?source .\n", " }\n", " } \n", "} group by ?juris\n", "\"\"\"\n", "\n", "run_query(query)\n", "\n" ] }, { "cell_type": "markdown", "id": "fad9450d", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### CQ13: What was the last legislation approved by the government of the Community of Madrid?" ] }, { "cell_type": "code", "execution_count": null, "id": "3e6aed30", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T12:03:16.030100Z", "start_time": "2024-02-06T12:03:00.292895Z" }, "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "\n", "\n", "SELECT ?auth (SAMPLE(?juris) as ?jurisdiction) (MAX(?date) AS ?date) (SAMPLE(?id) AS ?id) (SAMPLE(?source) AS ?source) (SAMPLE(?s_text) AS ?content) \n", "WHERE {\n", " {\n", " ?s a lkg:Legislation ;\n", " nif:isString ?s_text ;\n", " lkg:metadata ?metadata .\n", " ?metadata eli:jurisdiction ?juris ;\n", " eli:version_date ?date ;\n", " eli:id_local ?id ;\n", " lkg:hasAuthority ?auth;\n", " terms:source ?source .\n", " }\n", " UNION{\n", " SERVICE {\n", " ?s a lkg:Legislation ;\n", " nif:isString ?s_text ;\n", " lkg:metadata ?metadata .\n", " ?metadata eli:jurisdiction ?juris ;\n", " eli:version_date ?date ;\n", " eli:id_local ?id ;\n", " lkg:hasAuthority ?auth;\n", " terms:source ?source .\n", " }\n", " } FILTER(?auth=)\n", "}GROUP BY ?auth\n", "\"\"\"\n", "\n", "run_query(query)\n" ] }, { "cell_type": "markdown", "id": "95773e74", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### CQ14: What is the longest legislation?" ] }, { "cell_type": "code", "execution_count": null, "id": "159f3ffa", "metadata": { "ExecuteTime": { "end_time": "2023-12-21T13:16:19.741150Z", "start_time": "2023-12-21T13:16:04.097220Z" }, "hidden": true, "scrolled": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "\n", "\n", "SELECT (SAMPLE(?juris) as ?jurisdiction) (SAMPLE(?date) AS ?date) (SAMPLE(?id) AS ?id) \n", "(SAMPLE(?source) AS ?source) (MAX(STRLEN(?s_text)) AS ?len_s_text) (SAMPLE(?s_text) as ?content)\n", "WHERE {\n", " {\n", " ?s a lkg:Legislation ;\n", " nif:isString ?s_text ;\n", " lkg:metadata ?metadata .\n", " ?metadata eli:jurisdiction ?juris ;\n", " eli:version_date ?date ;\n", " eli:id_local ?id ;\n", " terms:source ?source .\n", " }\n", " UNION{\n", " SERVICE {\n", " ?s a lkg:Legislation ;\n", " nif:isString ?s_text ;\n", " lkg:metadata ?metadata .\n", " ?metadata eli:jurisdiction ?juris ;\n", " eli:version_date ?date ;\n", " eli:id_local ?id ;\n", " terms:source ?source .\n", " }\n", " } \n", "}\n", "\"\"\"\n", "\n", "run_query(query)\n" ] }, { "cell_type": "markdown", "id": "3160df4b", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### R1: Political discourse has different metrics (views, listeners, attendees, likes, etc.)" ] }, { "cell_type": "code", "execution_count": null, "id": "e3ba47ba", "metadata": { "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select DISTINCT ?metrics where { \n", " ?s a podio:Discourse;\n", " schema:interactionStatistic ?stats.\n", " ?stats a schema:InteractionCounter;\n", " schema:interactionType ?metrics.\n", "}\n", "\n", "\"\"\"\n", "\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "6e8937c2", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### R2: A speech is published by an agent who may not be the creator of the speech itself." ] }, { "cell_type": "code", "execution_count": null, "id": "4620e1c7", "metadata": { "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select DISTINCT ?s ?publisher ?creator where { \n", " ?s a podio:Discourse;\n", " terms:publisher ?publisher;\n", " terms:creator ?creator.\n", " FILTER(?publisher != ?creator)\n", "}\n", "\n", "\"\"\"\n", "\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "0b23be7e", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### R3: A speech has an audience. That is, the group of people who have received the message." ] }, { "cell_type": "code", "execution_count": null, "id": "5a5298d3", "metadata": { "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select DISTINCT ?audience where { \n", " ?s a podio:Discourse;\n", " terms:audience ?audience.\n", "}\n", "\n", "\"\"\"\n", "\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "80dcc938", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### R4: A speech has a target. That is, the group of people to whom the message is intended. This group does not necessarily have to coincide with the audience." ] }, { "cell_type": "code", "execution_count": null, "id": "a53c4201", "metadata": { "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select DISTINCT ?audience ?target where { \n", " ?s a podio:Discourse;\n", " terms:audience ?audience;\n", " podio:hasTarget ?target.\n", " FILTER(?target != ?audience)\n", "}\n", "\n", "\"\"\"\n", "\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "cac600cb", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### R5: Both speeches and party manifestos are written in one or more languages." ] }, { "cell_type": "code", "execution_count": null, "id": "7324a5f0", "metadata": { "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select DISTINCT ?language where { \n", " ?s a podio:Discourse;\n", " terms:language ?language.\n", "}\n", "\"\"\"\n", "\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "d7ddeab6", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### R6: Both speeches and party manifestos have a publication date." ] }, { "cell_type": "code", "execution_count": null, "id": "c563f7c8", "metadata": { "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select ?date where { \n", " ?s a podio:Discourse;\n", " terms:created ?date.\n", "} Limit 10\n", "\"\"\"\n", "\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "ff5dd4f5", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### R7: Both speeches and party manifestos can have a description." ] }, { "cell_type": "code", "execution_count": null, "id": "0b48972d", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T16:49:52.806604Z", "start_time": "2024-02-06T16:49:52.773220Z" }, "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select ?desc where { \n", " VALUES ?clases {\n", " podio:Discourse\n", " podio:PartyManifesto\n", " }\n", " ?s a ?clases;\n", " terms:description ?desc.\n", "} Limit 10\n", "\n", "\"\"\"\n", "\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "21b2387c", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T17:09:13.610230Z", "start_time": "2024-02-06T17:09:13.606913Z" }, "heading_collapsed": true, "hidden": true }, "source": [ "### R8: Both speeches and party manifestos have an ideology." ] }, { "cell_type": "code", "execution_count": null, "id": "c492ac14", "metadata": { "ExecuteTime": { "end_time": "2024-02-06T17:09:13.603052Z", "start_time": "2024-02-06T17:08:54.253934Z" }, "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select DISTINCT ?ideology ?ideologyLabel where { \n", " VALUES ?clases {\n", " podio:Discourse\n", " podio:PartyManifesto\n", " }\n", " ?s a ?clases;\n", " podio:ideology ?ideology.\n", " \n", " # Query Wikidata using federation\n", " SERVICE {\n", " ?ideology rdfs:label ?ideologyLabel.\n", " FILTER(LANGMATCHES(LANG(?ideologyLabel), \"en\")).\n", " SERVICE wikibase:label { bd:serviceParam wikibase:language \"en\". }\n", " }\n", " \n", "} Limit 3\n", "\n", "\"\"\"\n", "\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "77c46630", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### R9: Both speeches and party manifestos should reference the source of information in the official channel." ] }, { "cell_type": "code", "execution_count": null, "id": "4f55826a", "metadata": { "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select DISTINCT ?sources where { \n", " VALUES ?clases {\n", " podio:Discourse\n", " podio:PartyManifesto\n", " }\n", " ?s a ?clases;\n", " terms:source ?sources.\n", " \n", " \n", "} Limit 3\n", "\n", "\"\"\"\n", "\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "6a5d986a", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### R10: A party manifesto has a textual content extracted from a document." ] }, { "cell_type": "code", "execution_count": null, "id": "6c72b535", "metadata": { "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select DISTINCT ?content ?sources where { \n", " ?s a podio:PartyManifesto;\n", " podio:content ?content;\n", " terms:source ?sources.\n", "\n", "} Limit 3\n", "\"\"\"\n", "\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "1e1975c8", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### R11: A party manifesto proposes a candidate for political position." ] }, { "cell_type": "code", "execution_count": null, "id": "392260a5", "metadata": { "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select DISTINCT ?candidate ?candidateLabel ?sources where { \n", " ?s a podio:PartyManifesto;\n", " podio:proposesCandidate ?candidate;\n", " terms:source ?sources.\n", " \n", " # Query Wikidata using federation\n", " SERVICE {\n", " ?candidate rdfs:label ?candidateLabel.\n", " FILTER(LANGMATCHES(LANG(?candidateLabel), \"en\")).\n", " SERVICE wikibase:label { bd:serviceParam wikibase:language \"en\". }\n", " }\n", " \n", "} Limit 3\n", "\n", "\"\"\"\n", "\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "d04b715c", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### R12: A party manifesto is published by the political party that drafts it." ] }, { "cell_type": "code", "execution_count": null, "id": "f42867a7", "metadata": { "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select DISTINCT ?publisher ?publisherLabel ?sources where { \n", " ?s a podio:PartyManifesto;\n", " terms:publisher ?publisher.\n", " \n", " # Query Wikidata using federation\n", " SERVICE {\n", " ?publisher rdfs:label ?publisherLabel.\n", " FILTER(LANGMATCHES(LANG(?publisherLabel), \"en\")).\n", " SERVICE wikibase:label { bd:serviceParam wikibase:language \"en\". }\n", " }\n", " \n", "} Limit 3\n", "\"\"\"\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "653b4f17", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### R13: A party manifesto has several policy proposals." ] }, { "cell_type": "code", "execution_count": null, "id": "de532edc", "metadata": { "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select DISTINCT ?pmanifest ?proposal ?proposalContent where { \n", " ?pmanifest a podio:PartyManifesto.\n", " \n", " ?proposal terms:isPartOf ?pmanifest;\n", " podio:content ?proposalContent.\n", " \n", " \n", "} Limit 3\n", "\"\"\"\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "9b10f19b", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### R14: Political speech can have content in any format, both text and multimedia." ] }, { "cell_type": "code", "execution_count": null, "id": "0acaac39", "metadata": { "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select DISTINCT ?content where { \n", " ?speech a podio:Discourse;\n", " podio:content ?content.\n", " \n", "} Limit 3\n", "\"\"\"\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "f6552fe8", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### R15: There are speeches that are shared in digital communities and allow direct interaction with the audience." ] }, { "cell_type": "code", "execution_count": null, "id": "0ea88c5e", "metadata": { "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select DISTINCT ?content where { \n", " ?speech a podio:Conversational;\n", " podio:content ?content.\n", " \n", "} Limit 3\n", "\"\"\"\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "68d562d3", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### R16: There are speeches that may be shared on channels that do not allow interaction with the audience." ] }, { "cell_type": "code", "execution_count": null, "id": "b3178478", "metadata": { "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select DISTINCT ?content where { \n", " ?speech a podio:Expository;\n", " podio:content ?content.\n", " \n", "} Limit 3\n", "\"\"\"\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "64209ba0", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### R17: Speeches shared in digital communities should implement the basic mechanics of interaction (reply, mention, thread, hashtags, post, repost, follow, and share content)." ] }, { "cell_type": "code", "execution_count": null, "id": "7bf6f9a9", "metadata": { "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select DISTINCT ?p where { \n", " ?speech a podio:Conversational;\n", " ?p ?o.\n", " \n", "} \n", "\n", "\"\"\"\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "7800861c", "metadata": { "heading_collapsed": true, "hidden": true }, "source": [ "### R18: The laws approved by political parties and their electoral proposals are speeches that do not allow for direct interaction with the audience." ] }, { "cell_type": "code", "execution_count": null, "id": "1d8c8a24", "metadata": { "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "select DISTINCT ?speech where { \n", " VALUES ?clases {\n", " podio:PolicyProposal\n", " podio:ApprovedPolicy\n", " }\n", " ?speech a ?clases;\n", " a podio:Expository.\n", " \n", "} \n", "\"\"\"\n", "run_query(query)" ] }, { "cell_type": "markdown", "id": "3399e2fe", "metadata": { "hidden": true }, "source": [ "### R19: It should be possible to explore the existing laws in the Lynx knowledge graph." ] }, { "cell_type": "code", "execution_count": null, "id": "0d154bb6", "metadata": { "hidden": true }, "outputs": [], "source": [ "query= \"\"\"\n", "PREFIX dc: \n", "PREFIX dcam: \n", "PREFIX eli: \n", "PREFIX foaf: \n", "PREFIX lkg: \n", "PREFIX nif-core: \n", "PREFIX owl: \n", "PREFIX podio: \n", "PREFIX rdf: \n", "PREFIX schema: \n", "PREFIX sioc: \n", "PREFIX skos: \n", "PREFIX terms: \n", "PREFIX vann: \n", "PREFIX xml: \n", "PREFIX xsd: \n", "PREFIX rdfs: \n", "PREFIX nif: \n", "PREFIX wd: \n", "PREFIX wdt: \n", "PREFIX wikibase: \n", "PREFIX bd: \n", "\n", "SELECT (?juris as ?jurisdiction) ?year ?s_text\n", "WHERE {\n", " \n", " SERVICE {\n", " ?s a lkg:Legislation ;\n", " nif:isString ?s_text ;\n", " lkg:metadata ?metadata .\n", " ?metadata eli:jurisdiction ?juris ;\n", " eli:version_date ?date ;\n", " eli:id_local ?id ;\n", " terms:source ?source .\n", " }\n", " \n", " BIND(year(?date) as ?year)\n", " \n", "} LIMIT 10\n", "\"\"\"\n", "run_query(query)" ] } ], "metadata": { "hide_input": false, "kernelspec": { "display_name": "mets", "language": "python", "name": "mets" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.6" }, "toc": { "base_numbering": 1, "nav_menu": { "height": "319px", "width": "160px" }, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": false } }, "nbformat": 4, "nbformat_minor": 5 }