![\"Open](\"https://colab.research.google.com/assets/colab-badge.svg\"){kind=icon}
"
]
},
{
"cell_type": "code",
"metadata": {
"id": "3lyBiqUTGq-Y",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 204
},
"outputId": "d43b0f44-2a44-4ffc-d703-543739b340e8"
},
"source": [
"#@title @Author and building @date\n",
"!pip install watermark\n",
"%load_ext watermark\n",
"from IPython.display import clear_output;clear_output()\n",
"%watermark -a \"Romell D.Z.\" -u -d -p tweepy,scipy,nltk,gensim,sklearn,networkx,textblob,spacy"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"Romell D.Z. \n",
"last updated: 2020-10-09 \n",
"\n",
"tweepy 3.6.0\n",
"scipy 1.4.1\n",
"nltk 3.2.5\n",
"gensim 3.6.0\n",
"sklearn 0.0\n",
"networkx 2.5\n",
"textblob 0.15.3\n",
"spacy 2.2.4\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "aQe_NEVKHmlN",
"cellView": "form"
},
"source": [
"#@title Parameters\n",
"KEYWORD='podemos' #@param {type: \"string\"}\n",
"#@title \n",
"NUMBER_OF_TWEETS = 250 #@param {type: \"slider\", min: 250, max: 5000, step:250}\n",
"language = \"es\" #@param [\"es\", \"en\"] {allow-input: false}\n",
"GEO_LOCATION_BOUNDING_BOX = [-82.1,-18.4,-68.3,-3.1] #@param {type: \"string\"}"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "_wIAMCKgl2al",
"cellView": "form"
},
"source": [
"#@title Insert your gist which contains .netrc\n",
"%%capture\n",
"import os, netrc\n",
"gist = '' #@param {type: \"string\"}\n",
"!wget https://gist.githubusercontent.com/romellfudi/{gist}/raw/.tweet.netrc -O .netrc\n",
"file = \".netrc\" if os.path.isfile(\".netrc\") else None\n",
"auth = netrc.netrc(file)\n",
"ckey,_,csecret=auth.authenticators('tweet_api')\n",
"atoken,_,asecret=auth.authenticators('tweet_secret')"
],
"execution_count": 5,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "7HkqhZMUGq-j"
},
"source": [
"#@title Load libraries\n",
"%%capture\n",
"!pip install unidecode pyLDAvis pyprind networkx advertools\n",
"!pip install deplacy\n",
"if language == 'en':\n",
" !python -m spacy download en_core_web_sm\n",
"else:\n",
" !python -m spacy download es_core_news_sm\n",
"!mkdir snapshot/\n",
"import os\n",
"import tweepy\n",
"from tweepy import Stream\n",
"from unidecode import unidecode\n",
"import re\n",
"from tweepy import StreamListener\n",
"from pprint import pprint\n",
"import pyprind\n",
"import pandas as pd\n",
"import random\n",
"from scipy.stats import beta as beta_distribution\n",
"import numpy as np\n",
"from textblob import TextBlob\n",
"from nltk.corpus import stopwords \n",
"from nltk import word_tokenize\n",
"from nltk.data import load\n",
"from nltk.stem import SnowballStemmer\n",
"from nltk.stem.wordnet import WordNetLemmatizer\n",
"import string\n",
"import gensim\n",
"from gensim import corpora\n",
"\n",
"import pyLDAvis\n",
"import pyLDAvis.gensim # don't skip this\n",
"\n",
"from gensim.models.ldamodel import LdaModel\n",
"from string import punctuation\n",
"from sklearn.feature_extraction.text import CountVectorizer\n",
"\n",
"from sklearn.pipeline import Pipeline\n",
"from sklearn.svm import LinearSVC\n",
"from sklearn.model_selection import GridSearchCV\n",
"from textblob import Word\n",
"from textblob import TextBlob\n",
"from sklearn.feature_extraction.text import TfidfVectorizer\n",
"\n",
"from sklearn.manifold import TSNE\n",
"import matplotlib.pyplot as plt\n",
"import advertools as adv\n",
"import networkx as nx\n",
"import warnings\n",
"warnings.simplefilter('ignore')\n",
"import pkg_resources,imp\n",
"imp.reload(pkg_resources)\n",
"import spacy\n",
"from spacy import displacy\n",
"if language == 'en':\n",
" nlp = spacy.load('en_core_web_sm') \n",
"else:\n",
" nlp = spacy.load('es_core_news_sm')\n",
"nltk.download('punkt')\n",
"%matplotlib inline\n",
"# from textblob import TextBlob\n",
"# TextBlob(\"bonjour esto es una 我 它\").detect_language()"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "NQwcnzYmGq-p"
},
"source": [
"# [BoundingBox](https://boundingbox.klokantech.com/) CSV RAW"
]
},
{
"cell_type": "code",
"metadata": {
"id": "WdhD7uzcGq-p"
},
"source": [
"auth = tweepy.OAuthHandler(ckey, csecret)\n",
"auth.set_access_token(atoken, asecret)\n",
"api = tweepy.API(auth)"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "4YW2y9MKGq-4"
},
"source": [
"class FiniteStreamListener(StreamListener):\n",
" \n",
" def __init__(self, number_of_tweets):\n",
" self.number_of_tweets = number_of_tweets\n",
" self.tweets = []\n",
" self.tweets_dict = []\n",
" pbar = pyprind.ProgBar(number_of_tweets)\n",
" super(FiniteStreamListener,self).__init__()\n",
" \n",
" def on_status(self, status):\n",
" if len(self.tweets) < self.number_of_tweets:\n",
" # if TextBlob(status.text).detect_language() == 'es':\n",
" self.tweets_dict.append(status._json)\n",
" place = status._json['place']['name'] if(status._json['place']) else \"\"\n",
" self.tweets.append({'date':status.created_at,\n",
" 'text':status.text,\n",
" 'location':place,\n",
" 'followers':status._json['user']['followers_count']})\n",
" pbar.update()\n",
" else:\n",
" return False"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "B4Jo4Pw6Gq-7"
},
"source": [
"finite_stream_listener = FiniteStreamListener(number_of_tweets=NUMBER_OF_TWEETS)\n",
"streaming_api = Stream(auth=auth, listener=finite_stream_listener,timeout=5) #60"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "RVqBos_wGq-_"
},
"source": [
"### The streaming API doesn't allow to filter by location AND keyword simultaneously."
]
},
{
"cell_type": "code",
"metadata": {
"id": "QK5z4Ou3Gq-_"
},
"source": [
"finite_stream_listener.tweets = []\n",
"EMOTICONS = \">:] :-) :) :o) :] :3 :c) :> =] 8) =) :} :^) \"\n",
"EMOTICONS = EMOTICONS.strip().split(' ')\n",
"# streaming_api.filter(track=EMOTICONS,languages=[language],async=True)\n",
"# streaming_api.filter(locations=GEO_LOCATION_BOUNDING_BOX,languages=[language],async=True)\n",
"streaming_api.filter(locations=GEO_LOCATION_BOUNDING_BOX,track=EMOTICONS, languages=[language],async=True)"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "-Kuo8f7eMycB",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 68
},
"outputId": "93576c5d-e218-4cca-e3cc-71bed9c83060"
},
"source": [
"print(len(finite_stream_listener.tweets))\n",
"# 0% [##############################] 100% | ETA: 00:00:00\n",
"# Total time elapsed: 01:05:42 \n",
"random.sample([t['text'] for t in finite_stream_listener.tweets],2)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"200\n"
],
"name": "stdout"
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"['RT @ghwtss__: en fin, orgullosa de que esto pasó en Perú :) https://t.co/vSguM7Znti',\n",
" 'RT @sheila_Corzo: Quiero amigos de twitter :) digan hola.\\U0001f97a']"
]
},
"metadata": {
"tags": []
},
"execution_count": 65
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "kVQU0KViGq_N"
},
"source": [
"np.save('tweets_dict',finite_stream_listener.tweets_dict)"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "HkstNvrtGq_Q"
},
"source": [
"def make_lowercase(tweet):\n",
" return tweet.lower()\n",
"\n",
"def remove_diacritics(tweet):\n",
" return unidecode(tweet)\n",
"\n",
"def remove_non_alpha_characters(tweet):\n",
" return ''.join(character for character in tweet if character.isalpha() or character == ' ')\n",
"\n",
"def remove_web_site(tweet):\n",
" return re.sub(r'http\\w+', '', tweet)#, flags=re.MULTILINE)"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "t-8gwW6SGq_T"
},
"source": [
"tweets_df = pd.DataFrame.from_dict(finite_stream_listener.tweets)\n",
"tweets_df.rename(columns={'text':'Tweets'},inplace=True)"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "CcQmFTC7Gq_V"
},
"source": [
"tweets_df['word_count'] = tweets_df['Tweets'].apply(lambda x: len(str(x).split(\" \")))\n",
"tweets_df['char_count'] = tweets_df['Tweets'].str.len()\n",
"\n",
"def avg_word(sentence):\n",
" words = sentence.split()\n",
" return (sum(len(word) for word in words)/len(words))\n",
"\n",
"tweets_df['avg_word'] = tweets_df['Tweets'].apply(lambda x: avg_word(x))\n",
"tweets_df['hastags'] = tweets_df['Tweets'].apply(lambda x: len([x for x in x.split() if x.startswith('#')]))\n",
"tweets_df['numerics'] = tweets_df['Tweets'].apply(lambda x: len([x for x in x.split() if x.isdigit()]))"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "DZHeGLcgGq_a"
},
"source": [
"cleaned_tweets = list(tweets_df['Tweets'])\n",
"for cleaning_function in \\\n",
" [make_lowercase, \n",
" remove_diacritics,\n",
" remove_non_alpha_characters,\n",
" remove_web_site]:\n",
" cleaned_tweets = [cleaning_function(tweet) for tweet in cleaned_tweets]"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "jRBvHlfyGq_d",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 68
},
"outputId": "aa29d573-cb53-4341-fdd7-20d23807913d"
},
"source": [
"random.sample(cleaned_tweets,3)"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"['lovelymink hola remi nos ensenaras a cocinar ',\n",
" 'el pedo de acomodar eso es que esta termina siendo la cena ',\n",
" 'tejadaguadalup pa mi sos la o ']"
]
},
"metadata": {
"tags": []
},
"execution_count": 289
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "DbdB1ODOkuEO",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"outputId": "e0ce4822-89b0-4fca-a9f5-58d5747125b0"
},
"source": [
"KEYWORD = make_lowercase(remove_diacritics(remove_non_alpha_characters(remove_web_site(KEYWORD))))\n",
"KEYWORD"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"application/vnd.google.colaboratory.intrinsic+json": {
"type": "string"
},
"text/plain": [
"'podemos'"
]
},
"metadata": {
"tags": []
},
"execution_count": 108
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "zisW-O4bGq_g",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 51
},
"outputId": "1cd26ed3-a5ce-4cbc-a87e-c8a13dfd1f11"
},
"source": [
"number_of_occurences = sum('peru' in tweet for tweet in cleaned_tweets)\n",
"print('Nuestra palabra clave aparece: {} veces'.format(number_of_occurences))\n",
"print('Nuestra palabra clave apareció en: {}% de los tweets'.format(100 * number_of_occurences/NUMBER_OF_TWEETS))"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"Nuestra palabra clave aparece: 5 veces\n",
"Nuestra palabra clave apareció en: 2.5% de los tweets\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "qo2z0PJ0Gq_j",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 119
},
"outputId": "144fca34-ca4c-4fac-b848-640dcc8566b2"
},
"source": [
"pprint([tweet for tweet in cleaned_tweets if KEYWORD in tweet][:number_of_occurences//2+1])"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"['rt romerotroll vamos amigoooos si podemos logra ese numero canciones para '\n",
" 'mi ex rt ',\n",
" 'rt romerotroll vamos amigoooos si podemos logra ese numero canciones para '\n",
" 'mi ex rt ',\n",
" 'rt romerotroll vamos amigoooos si podemos logra ese numero canciones para '\n",
" 'mi ex rt ']\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "5r_LrvUBGq_5",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"outputId": "4ea63b9f-ef5d-466a-96f9-bd428927e569"
},
"source": [
"indices_of_tweets_containing_keyword=[index for index, tweet in enumerate(cleaned_tweets) if KEYWORD in tweet]\n",
"print('index de los 10 tweets:%s'%(indices_of_tweets_containing_keyword))"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"index de los 10 tweets:[0, 2, 20, 22, 24, 30, 41, 65, 86, 116, 121, 130, 139, 148]\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "6TZPwnPhGq__"
},
"source": [
"distances_between_indices_of_tweets_containing_keyword = [\n",
" second_index - first_index for first_index, second_index in \\\n",
" zip(indices_of_tweets_containing_keyword[:-1], indices_of_tweets_containing_keyword[1:])\n",
"]"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "PYv77BARGrAG",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 265
},
"outputId": "fb678f3b-9a12-447e-8ecf-506a6fc69714"
},
"source": [
"pd.Series(distances_between_indices_of_tweets_containing_keyword).hist()\n",
"plt.savefig('snapshot/lima_tweets_hist.png')"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"| \n", " | date | \n", "Tweets | \n", "location | \n", "followers | \n", "word_count | \n", "char_count | \n", "avg_word | \n", "hastags | \n", "numerics | \n", "Tweets_clean | \n", "
|---|---|---|---|---|---|---|---|---|---|---|
| 4 | \n", "2020-10-09 04:11:20 | \n", "Poco a poco todo se va acomodando | \n", "Santa Anita | \n", "170 | \n", "2 | \n", "13 | \n", "6.000000 | \n", "0 | \n", "0 | \n", "va acomodando | \n", "
| 11 | \n", "2020-10-09 04:11:25 | \n", "Hay gente que han perdido la vergüenza, preten... | \n", "Jesús Maria | \n", "51 | \n", "7 | \n", "51 | \n", "6.428571 | \n", "0 | \n", "0 | \n", "gente perdido vergüenza pretender ser candidat... | \n", "
| 12 | \n", "2020-10-09 04:11:25 | \n", "Éste Viernes de Sankirtana, nos visita Hanumat... | \n", "Lurigancho | \n", "401 | \n", "14 | \n", "116 | \n", "7.357143 | \n", "0 | \n", "0 | \n", "éste viernes sankirtana visita hanumat prana d... | \n", "
| \n", " | Tweets_clean | \n", "NOUNS | \n", "ACTIONS | \n", "
|---|---|---|---|
| 4 | \n", "va acomodando | \n", "desgracia | \n", "cuídate | \n", "
| 11 | \n", "gente perdido vergüenza pretender ser candidat... | \n", "NaN | \n", "NaN | \n", "
| 12 | \n", "éste viernes sankirtana visita hanumat prana d... | \n", "piqueos, basura | \n", "comer | \n", "
| 14 | \n", "untkcqr emilia14614784 luvwaifus cuídate anja ... | \n", "NaN | \n", "hagan | \n", "
| 33 | \n", "ohohuh1 cuídate mucho desgracia todo | \n", "NaN | \n", "NaN | \n", "
| \n", " | date | \n", "Tweets | \n", "location | \n", "followers | \n", "word_count | \n", "char_count | \n", "avg_word | \n", "hastags | \n", "numerics | \n", "Tweets_clean | \n", "ACTIONS | \n", "NOUNS | \n", "
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 4 | \n", "2020-10-09 04:11:20 | \n", "Poco a poco todo se va acomodando | \n", "Santa Anita | \n", "170 | \n", "2 | \n", "13 | \n", "6.000000 | \n", "0 | \n", "0 | \n", "va acomodando | \n", "cuídate | \n", "desgracia | \n", "
| 11 | \n", "2020-10-09 04:11:25 | \n", "Hay gente que han perdido la vergüenza, preten... | \n", "Jesús Maria | \n", "51 | \n", "7 | \n", "51 | \n", "6.428571 | \n", "0 | \n", "0 | \n", "gente perdido vergüenza pretender ser candidat... | \n", "NaN | \n", "NaN | \n", "
| 12 | \n", "2020-10-09 04:11:25 | \n", "Éste Viernes de Sankirtana, nos visita Hanumat... | \n", "Lurigancho | \n", "401 | \n", "14 | \n", "116 | \n", "7.357143 | \n", "0 | \n", "0 | \n", "éste viernes sankirtana visita hanumat prana d... | \n", "comer | \n", "piqueos, basura | \n", "
| 14 | \n", "2020-10-09 04:11:27 | \n", "@UnTkCqr @Emilia14614784 @LuvWaifus Cuídate mu... | \n", "Villa el Salvador | \n", "371 | \n", "13 | \n", "107 | \n", "7.307692 | \n", "0 | \n", "0 | \n", "untkcqr emilia14614784 luvwaifus cuídate anja ... | \n", "hagan | \n", "NaN | \n", "
| 33 | \n", "2020-10-09 04:11:43 | \n", "@ohohuh1 :( cuídate mucho.\\n\\nQué desgracia, t... | \n", "Magdalena del Mar | \n", "196 | \n", "5 | \n", "36 | \n", "6.400000 | \n", "0 | \n", "0 | \n", "ohohuh1 cuídate mucho desgracia todo | \n", "NaN | \n", "NaN | \n", "
| \n", " | words | \n", "tf | \n", "idf | \n", "tfidf | \n", "
|---|---|---|---|---|
| 0 | \n", "acomodando | \n", "1.0 | \n", "0.693147 | \n", "0.693147 | \n", "
| 1 | \n", "va | \n", "1.0 | \n", "0.693147 | \n", "0.693147 | \n", "
| 2 | \n", "perú | \n", "1.0 | \n", "0.693147 | \n", "0.693147 | \n", "
| 3 | \n", "gran | \n", "1.0 | \n", "0.693147 | \n", "0.693147 | \n", "
| 4 | \n", "sankirtanero | \n", "1.0 | \n", "0.693147 | \n", "0.693147 | \n", "
| 5 | \n", "da | \n", "1.0 | \n", "0.000000 | \n", "0.000000 | \n", "
| 6 | \n", "méxico | \n", "1.0 | \n", "0.693147 | \n", "0.693147 | \n", "
| 7 | \n", "hanumat | \n", "1.0 | \n", "0.693147 | \n", "0.693147 | \n", "
| 8 | \n", "éste | \n", "1.0 | \n", "0.693147 | \n", "0.693147 | \n", "
| 9 | \n", "colombi… | \n", "1.0 | \n", "0.693147 | \n", "0.693147 | \n", "
| \n", " | date | \n", "Tweets | \n", "location | \n", "followers | \n", "word_count | \n", "char_count | \n", "avg_word | \n", "hastags | \n", "numerics | \n", "Tweets_clean | \n", "ACTIONS | \n", "NOUNS | \n", "
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2 | \n", "2020-10-09 04:11:25 | \n", "Éste Viernes de Sankirtana, nos visita Hanumat... | \n", "Lurigancho | \n", "401 | \n", "14 | \n", "116 | \n", "7.357143 | \n", "0 | \n", "0 | \n", "éste viernes sankirtana visita hanumat prana d... | \n", "comer | \n", "piqueos, basura | \n", "
| \n", " | Tweets | \n", "score | \n", "
|---|---|---|
| 2 | \n", "Éste Viernes de Sankirtana, nos visita Hanumat Prana Das, un gran y entusiasta sankirtanero. \\nPerú /México /Colombi... | \n", "NaN | \n", "
| 1 | \n", "NaN | \n", "0.0 | \n", "
| \n", " | Noun | \n", "Freq | \n", "
|---|---|---|
| 0 | \n", "desgracia | \n", "1 | \n", "
| 1 | \n", "piqueos | \n", "1 | \n", "
| 2 | \n", "basura | \n", "1 | \n", "
| \n", " | date | \n", "Tweets | \n", "location | \n", "followers | \n", "word_count | \n", "char_count | \n", "avg_word | \n", "hastags | \n", "numerics | \n", "Tweets_clean | \n", "ACTIONS | \n", "NOUNS | \n", "
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", "2020-10-09 04:11:20 | \n", "Poco a poco todo se va acomodando | \n", "Santa Anita | \n", "170 | \n", "2 | \n", "13 | \n", "6.0 | \n", "0 | \n", "0 | \n", "va acomodando | \n", "cuídate | \n", "desgracia | \n", "
| \n", " | Tweets | \n", "followers | \n", "hashtags | \n", "hashcounts | \n", "mentions | \n", "mention_count | \n", "emoji | \n", "emoji_text | \n", "emoji_count | \n", "
|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", "Poco a poco todo se va acomodando | \n", "170 | \n", "[] | \n", "0 | \n", "[] | \n", "0 | \n", "[] | \n", "[] | \n", "0 | \n", "
| 1 | \n", "Hay gente que han perdido la vergüenza, pretender ser candidato de UPP. | \n", "51 | \n", "[] | \n", "0 | \n", "[] | \n", "0 | \n", "[] | \n", "[] | \n", "0 | \n", "
| 2 | \n", "Éste Viernes de Sankirtana, nos visita Hanumat Prana Das, un gran y entusiasta sankirtanero. \\nPerú /México /Colombi... | \n", "401 | \n", "[] | \n", "0 | \n", "[] | \n", "0 | \n", "[] | \n", "[] | \n", "0 | \n", "
| 3 | \n", "@UnTkCqr @Emilia14614784 @LuvWaifus Cuídate mucho Anja. Recuerda que Emilia es la Best Girl de Re:Zero por muchas r…... | \n", "371 | \n", "[] | \n", "0 | \n", "[@untkcqr, @emilia14614784, @luvwaifus] | \n", "3 | \n", "[] | \n", "[] | \n", "0 | \n", "
| 4 | \n", "@ohohuh1 :( cuídate mucho.\\n\\nQué desgracia, todo... | \n", "196 | \n", "[] | \n", "0 | \n", "[@ohohuh1] | \n", "1 | \n", "[] | \n", "[] | \n", "0 | \n", "
| \n", " | word | \n", "abs_freq | \n", "wtd_freq | \n", "rel_value | \n", "
|---|
| \n", " | Tweets | \n", "followers | \n", "hashtags | \n", "hashcounts | \n", "mentions | \n", "mention_count | \n", "emoji | \n", "emoji_text | \n", "emoji_count | \n", "
|---|
| \n", " | word | \n", "abs_freq | \n", "wtd_freq | \n", "rel_value | \n", "
|---|---|---|---|---|
| 0 | \n", "@daniloruiz1924 | \n", "1 | \n", "6014 | \n", "6014.0 | \n", "
| 1 | \n", "@universitario | \n", "1 | \n", "6014 | \n", "6014.0 | \n", "
| 2 | \n", "@gordoomx | \n", "1 | \n", "2161 | \n", "2161.0 | \n", "
| 3 | \n", "@manago72 | \n", "1 | \n", "2161 | \n", "2161.0 | \n", "
| 4 | \n", "@emilia14614784 | \n", "1 | \n", "371 | \n", "371.0 | \n", "
| 5 | \n", "@untkcqr | \n", "1 | \n", "371 | \n", "371.0 | \n", "
| 6 | \n", "@luvwaifus | \n", "1 | \n", "371 | \n", "371.0 | \n", "
| 7 | \n", "@marlovilela | \n", "1 | \n", "329 | \n", "329.0 | \n", "
| 8 | \n", "@seleccionperu | \n", "1 | \n", "329 | \n", "329.0 | \n", "
| 9 | \n", "@ohohuh1 | \n", "1 | \n", "196 | \n", "196.0 | \n", "
| \n", " | word | \n", "abs_freq | \n", "wtd_freq | \n", "rel_value | \n", "
|---|---|---|---|---|
| 0 | \n", "👏 | \n", "3 | \n", "6483 | \n", "2161.0 | \n", "
| 1 | \n", "🙏 | \n", "2 | \n", "4322 | \n", "2161.0 | \n", "
| 2 | \n", "🥺 | \n", "1 | \n", "2161 | \n", "2161.0 | \n", "
| 3 | \n", "🍔 | \n", "1 | \n", "2161 | \n", "2161.0 | \n", "
| 4 | \n", "😋 | \n", "1 | \n", "2161 | \n", "2161.0 | \n", "
| 5 | \n", "🌛 | \n", "1 | \n", "2161 | \n", "2161.0 | \n", "
| 6 | \n", "🤣 | \n", "7 | \n", "1946 | \n", "278.0 | \n", "
| 7 | \n", "😍 | \n", "1 | \n", "155 | \n", "155.0 | \n", "
| 8 | \n", "🤦🏻♂️ | \n", "1 | \n", "136 | \n", "136.0 | \n", "
| 9 | \n", "😪 | \n", "1 | \n", "135 | \n", "135.0 | \n", "
| \n", " | word | \n", "abs_freq | \n", "wtd_freq | \n", "rel_value | \n", "emoji_text | \n", "
|---|---|---|---|---|---|
| 0 | \n", "👏 | \n", "3 | \n", "6483 | \n", "2161.0 | \n", "clapping hands | \n", "
| 1 | \n", "🙏 | \n", "2 | \n", "4322 | \n", "2161.0 | \n", "folded hands | \n", "
| 2 | \n", "🥺 | \n", "1 | \n", "2161 | \n", "2161.0 | \n", "pleading face | \n", "
| 3 | \n", "🍔 | \n", "1 | \n", "2161 | \n", "2161.0 | \n", "hamburger | \n", "
| 4 | \n", "😋 | \n", "1 | \n", "2161 | \n", "2161.0 | \n", "face savoring food | \n", "
| 5 | \n", "🌛 | \n", "1 | \n", "2161 | \n", "2161.0 | \n", "first quarter moon face | \n", "
| 6 | \n", "🤣 | \n", "7 | \n", "1946 | \n", "278.0 | \n", "rolling on the floor laughing | \n", "
| 7 | \n", "😍 | \n", "1 | \n", "155 | \n", "155.0 | \n", "smiling face with heart-eyes | \n", "
| 8 | \n", "🤦🏻♂️ | \n", "1 | \n", "136 | \n", "136.0 | \n", "person facepalming | \n", "
| 9 | \n", "😪 | \n", "1 | \n", "135 | \n", "135.0 | \n", "sleepy face | \n", "
| \n", " | created_at | \n", "id | \n", "id_str | \n", "text | \n", "source | \n", "truncated | \n", "in_reply_to_status_id | \n", "in_reply_to_status_id_str | \n", "in_reply_to_user_id | \n", "in_reply_to_user_id_str | \n", "in_reply_to_screen_name | \n", "user-id | \n", "user-id_str | \n", "user-name | \n", "user-screen_name | \n", "user-location | \n", "user-url | \n", "user-description | \n", "user-translator_type | \n", "user-protected | \n", "user-verified | \n", "user-followers_count | \n", "user-friends_count | \n", "user-listed_count | \n", "user-favourites_count | \n", "user-statuses_count | \n", "user-created_at | \n", "user-utc_offset | \n", "user-time_zone | \n", "user-geo_enabled | \n", "user-lang | \n", "user-contributors_enabled | \n", "user-is_translator | \n", "user-profile_background_color | \n", "user-profile_background_image_url | \n", "user-profile_background_image_url_https | \n", "user-profile_background_tile | \n", "user-profile_link_color | \n", "user-profile_sidebar_border_color | \n", "user-profile_sidebar_fill_color | \n", "... | \n", "quoted_status-is_quote_status | \n", "quoted_status-quote_count | \n", "quoted_status-reply_count | \n", "quoted_status-retweet_count | \n", "quoted_status-favorite_count | \n", "quoted_status-entities | \n", "quoted_status-favorited | \n", "quoted_status-retweeted | \n", "quoted_status-filter_level | \n", "quoted_status-lang | \n", "quoted_status_permalink-url | \n", "quoted_status_permalink-expanded | \n", "quoted_status_permalink-display | \n", "quoted_status-extended_tweet | \n", "quoted_status-possibly_sensitive | \n", "display_text_range | \n", "extended_tweet-full_text | \n", "extended_tweet-display_text_range | \n", "extended_tweet-entities | \n", "possibly_sensitive | \n", "retweeted_status-extended_entities | \n", "entities-media | \n", "extended_entities-media | \n", "quoted_status-extended_entities | \n", "quoted_status-quoted_status_id | \n", "quoted_status-quoted_status_id_str | \n", "extended_tweet-extended_entities | \n", "place-id | \n", "place-url | \n", "place-place_type | \n", "place-name | \n", "place-full_name | \n", "place-country_code | \n", "place-country | \n", "place-bounding_box | \n", "place-attributes | \n", "geo-type | \n", "geo-coordinates | \n", "coordinates-type | \n", "coordinates-coordinates | \n", "
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", "Fri Oct 09 03:56:50 +0000 2020 | \n", "1314414491648565248 | \n", "1314414491648565248 | \n", "RT @lovtyholic: ‼️‼️ayuden a reportar esta cuenta NO INTERACTUAR NO CITAR NO RESPONDER solo reporten el tweet y la c... | \n", "<a href=\"http://twitter.com/download/android\" rel=\"nofollow\">Twitter for Android</a> | \n", "False | \n", "NaN | \n", "None | \n", "NaN | \n", "None | \n", "None | \n", "3276878238 | \n", "3276878238 | \n", "HELLO JONGDAE 𐂅 | \n", "moonsootyong | \n", "None | \n", "https://invisiblestring.carrd.co | \n", "#도경수 🐧 -108 ۵she/her۵MoonDanSe|Tyongf♥️ #문태일 #태용 #정한 #เตนล์ ... | \n", "none | \n", "False | \n", "False | \n", "143 | \n", "198 | \n", "3 | \n", "90612 | \n", "20735 | \n", "Sun Jul 12 01:50:27 +0000 2015 | \n", "None | \n", "None | \n", "False | \n", "None | \n", "False | \n", "False | \n", "000000 | \n", "http://abs.twimg.com/images/themes/theme1/bg.png | \n", "https://abs.twimg.com/images/themes/theme1/bg.png | \n", "False | \n", "F58EA8 | \n", "000000 | \n", "000000 | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
| 1 | \n", "Fri Oct 09 03:56:50 +0000 2020 | \n", "1314414494039314432 | \n", "1314414494039314432 | \n", "¿qué hora es en su país cuando ven este tweet??? aquí son las 10:56 | \n", "<a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a> | \n", "False | \n", "NaN | \n", "None | \n", "NaN | \n", "None | \n", "None | \n", "1230697673105133570 | \n", "1230697673105133570 | \n", "𝐋𝐢𝐬𝐚 ♡𝐀𝐑𝐌𝐘 | \n", "Winter_bear1997 | \n", "None | \n", "None | \n", "𝑌𝑜𝑢’𝑣𝑒 𝑠𝘩𝑜𝑤𝑛 𝑚𝑒 𝐼 𝘩𝑎𝑣𝑒 𝑟𝑒𝑎𝑠𝑜𝑛𝑠 𝐼 𝑠𝘩𝑜𝑢𝑙𝑑 𝑙𝑜𝑣𝑒 𝑚𝑦𝑠𝑒𝑙f 𝐎𝐓𝟕 𝐒𝐭𝐚𝐧 𝐹𝑎𝑛 𝑎𝑐𝑐𝑜𝑢𝑛𝑡 | \n", "none | \n", "False | \n", "False | \n", "3503 | \n", "1969 | \n", "35 | \n", "13784 | \n", "8151 | \n", "Fri Feb 21 03:36:22 +0000 2020 | \n", "None | \n", "None | \n", "False | \n", "None | \n", "False | \n", "False | \n", "F5F8FA | \n", "\n", " | \n", " | False | \n", "1DA1F2 | \n", "C0DEED | \n", "DDEEF6 | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
| 2 | \n", "Fri Oct 09 03:56:51 +0000 2020 | \n", "1314414496002322432 | \n", "1314414496002322432 | \n", "RT @Juuandedios_p: Este tweet podra llegar a 500 comentarios con la siguiente frase:\\n\\nCANCIONES PARA MI EX\\n\\n15 c... | \n", "<a href=\"http://twitter.com/download/android\" rel=\"nofollow\">Twitter for Android</a> | \n", "False | \n", "NaN | \n", "None | \n", "NaN | \n", "None | \n", "None | \n", "1268048343202009088 | \n", "1268048343202009088 | \n", "𝙚𝙙𝙖🦋 | \n", "edaloveskenia | \n", "None | \n", "None | \n", "•𝐜𝐮𝐞𝐧𝐭𝐚 𝐩𝐚𝐫𝐚 𝐯𝐨𝐭𝐨𝐬•\\n𝐜𝐮𝐞𝐧𝐭𝐚 𝐩𝐫𝐢𝐧𝐜𝐢𝐩𝐚𝐥: @edapdc1\\n 𝐟𝐚𝐧 𝐚𝐜𝐜𝐨𝐮𝐧𝐭 | \n", "none | \n", "False | \n", "False | \n", "107 | \n", "136 | \n", "0 | \n", "80 | \n", "3584 | \n", "Wed Jun 03 05:14:31 +0000 2020 | \n", "None | \n", "None | \n", "False | \n", "None | \n", "False | \n", "False | \n", "F5F8FA | \n", "\n", " | \n", " | False | \n", "1DA1F2 | \n", "C0DEED | \n", "DDEEF6 | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
3 rows × 160 columns
\n", "| \n", " | user-screen_name | \n", "retweeted_status-user-screen_name | \n", "
|---|---|---|
| 0 | \n", "moonsootyong | \n", "whotamelonsugar | \n", "
| 1 | \n", "Winter_bear1997 | \n", "YoceOs | \n", "
| 2 | \n", "edaloveskenia | \n", "Constanpr | \n", "
| 3 | \n", "LeeBer37753434 | \n", "leonXD__ | \n", "
| 4 | \n", "FelipeCucalon | \n", "Michi_Ca_Pin | \n", "
| \n", " | screen_name | \n", "degree_centrality | \n", "
|---|---|---|
| 14 | \n", "corzin443 | \n", "0.134354 | \n", "
| 7 | \n", "leonXD__ | \n", "0.127551 | \n", "
| 1 | \n", "whotamelonsugar | \n", "0.119048 | \n", "
| 5 | \n", "Constanpr | \n", "0.103741 | \n", "
| 34 | \n", "Danna_ArdilaO | \n", "0.102041 | \n", "
| \n", " | screen_name | \n", "degree_centrality | \n", "
|---|---|---|
| 1 | \n", "None | \n", "0.570856 | \n", "
| 111 | \n", "leoni70803995 | \n", "0.002674 | \n", "
| 369 | \n", "lovely_min_k | \n", "0.002674 | \n", "
| 546 | \n", "jmvalerapiedras | \n", "0.002674 | \n", "
| 62 | \n", "jimenaajimenezr | \n", "0.002674 | \n", "
| \n", " | screen_name | \n", "betweenness_centrality | \n", "
|---|---|---|
| 14 | \n", "corzin443 | \n", "0.004016 | \n", "
| 51 | \n", "kmiilinn | \n", "0.002161 | \n", "
| 9 | \n", "Michi_Ca_Pin | \n", "0.001792 | \n", "
| 1 | \n", "whotamelonsugar | \n", "0.001751 | \n", "
| 28 | \n", "Crackalaka2 | \n", "0.001686 | \n", "
| \n", " | screen_name | \n", "betweenness_centrality | \n", "
|---|---|---|
| 261 | \n", "rosamt5 | \n", "0.000002 | \n", "
| 509 | \n", "stigmxjk | \n", "0.000002 | \n", "
| 76 | \n", "LuSKabeche | \n", "0.000002 | \n", "
| 0 | \n", "moonsootyong | \n", "0.000000 | \n", "
| 502 | \n", "Castelopio | \n", "0.000000 | \n", "
| \n", " | screen_name | \n", "degree_rt | \n", "degree_reply | \n", "ratio | \n", "
|---|---|---|---|---|
| 14 | \n", "corzin443 | \n", "79 | \n", "1 | \n", "0.012658 | \n", "
| 1 | \n", "whotamelonsugar | \n", "70 | \n", "0 | \n", "0.000000 | \n", "
| 3 | \n", "YoceOs | \n", "51 | \n", "0 | \n", "0.000000 | \n", "
| 5 | \n", "Constanpr | \n", "61 | \n", "0 | \n", "0.000000 | \n", "
| 7 | \n", "leonXD__ | \n", "75 | \n", "0 | \n", "0.000000 | \n", "