{ "metadata": { "name": "", "signature": "sha256:37ee02e6fb92193a11345afa84e2addf4efa9aa4e3d5d21b8e62213be98610ae" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Classifying the HTRC Genre Word Frequencies" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook is a part of work being done for the [Trace of Theory project](https://github.com/htrc/ACS-TT), a collaboration between researchers of [NovelTM](http://novel-tm.ca/) and the HathiTrust Research Center ([HTRC](https://www.hathitrust.org/)). In particular, we are wanting to use both [supervised](https://en.wikipedia.org/wiki/Supervised_learning) and [unsupervised](https://en.wikipedia.org/wiki/Unsupervised_learning) machine learning techniques on HTRC texts to gain a better understanding of the extent and nature of theory in various genres.\n", "\n", "This notebook builds on the [Classifying Philosophical Texts](ClassifyingPhilosophicalText.ipynb) notebook where we looked at building a classifier for philosophical texts, based on a small training corpus. In this notebook we'll try to use a trained classifier to identify philosophical texts based on [genre-specific wordcounts for 178,381 volumes from the HathiTrust Digital Library](https://sharc.hathitrust.org/genre); the genres are fiction, drama and poetry." ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Building a Philosophical Classifier" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The first step is to (re)build our [philosophical classifier](ClassifyingPhilosophicalText.ipynb). It's worth reiterating that the classifier is being trained on a relatively small corpus (so isn't likely as representative as it might be) and that the new HTRC genre corpus is literature-specific (so a different kind of beast from our training corpus). Is it still useful as a classifier? that's part of what we'd like to find out.\n", "\n", "The classifier created below is essentially the [same](ClassifyingPhilosophicalText.ipynb) as before, though we'll use the [LinearSVC](http://scikit-learn.org/stable/modules/generated/sklearn.svm.LinearSVC.html) algorithm because it provides a way of not just classifying (philosophical or non-philosophical) but also of expressing a value for how philosophical or not the text is." ] }, { "cell_type": "code", "collapsed": false, "input": [ "import nltk\n", "from sklearn.feature_extraction.text import TfidfVectorizer\n", "from sklearn.svm import LinearSVC\n", "\n", "# define the training corpus to use (while filtering out our Philosohpical ouliers)\n", "philo_data_dir = \"../../data/philosophy\"\n", "philo_corpus = nltk.corpus.reader.plaintext.PlaintextCorpusReader(philo_data_dir+\"/texts\", \".*\\.txt\")\n", "filtered_fileids = [fileid for fileid in philo_corpus.fileids() if \"GameOfLogic\" not in fileid and \"ThusSpakeZarathustr\" not in fileid]\n", "\n", "# create TF-IDF (actually elative frequencies) vectorizer\n", "stopword_vectorizer = TfidfVectorizer(use_idf=False, stop_words=nltk.corpus.stopwords.words(\"english\"), max_features=10000)\n", "X_train = stopword_vectorizer.fit_transform([philo_corpus.raw(fileid) for fileid in filtered_fileids])\n", "philo_categories = [\"Philosophy\" if \"Philosophy\" in fileid else \"Other\" for fileid in filtered_fileids]\n", "\n", "# create a classiier\n", "philo_clf = LinearSVC(loss='l2', penalty=\"l2\", dual=False, tol=1e-3)\n", "philo_clf.fit(X_train, philo_categories)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 180, "text": [ "LinearSVC(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n", " intercept_scaling=1, loss='l2', multi_class='ovr', penalty='l2',\n", " random_state=None, tol=0.001, verbose=0)" ] } ], "prompt_number": 180 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Analyzing the HTRC Genre Corpus" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The HTRC Genre corpus is organized by genre (if you rsync the directory rather than just download the files from the web the files are organized into subfolders by genre). For each genre there's a metadata file with all the volumes for that genre and then a set of compressed archives (.tar.gz) organized by time slice. Our strategy here will be as follows:\n", "\n", "* for each genre folder (fiction, drama, poetery)\n", " * read the metadata file into a table\n", " * for each compressed archive in the genre folder (*.tar.gz)\n", " * for each tab-separated values file in the archive\n", " * create a pseudo text \n", " * for each word-count pair: add the word the specified number of times to our pseuedo text\n", " * produce a classifier decision (a value how philosophical the text is\n", " * add the prediction value to the corresponding row in the metadata table" ] }, { "cell_type": "code", "collapsed": false, "input": [ "from os import walk\n", "import pandas as pd\n", "from os.path import join\n", "import glob\n", "\n", "def get_genre_metadata_and_predictions(genre_dir, clf, vectorizer):\n", " metadatas = {}\n", " for (dirpath, dirnames, filenames) in walk(htrc_genre_dir):\n", " for genre in dirnames:\n", " genre_path = join(htrc_genre_dir, genre) \n", " metadata = pd.read_csv(join(genre_path, genre+\"_metadata.csv\"), index_col=0)\n", " metadata['prediction'] = [float(0)] * len(metadata)\n", " for tgz in glob.glob(join(genre_path,\"*.tar.gz\")):\n", " print(\"Analyzing \"+tgz)\n", " tar = tarfile.open(tgz, \"r:gz\")\n", " for tarinfo in tar:\n", " if tarinfo.isreg() and tarinfo.name.endswith(\"tsv\"):\n", "\n", " # read in the TSV file and expand the text (it would probably be quicker to\n", " # create a vectorizer that can use the feature counts directly, but oh well\n", " text = \"\"\n", " tsv = tar.extractfile(tarinfo)\n", " for line in tsv.readlines():\n", " word, count = line.decode(\"utf-8\").strip().split(\"\\t\")\n", " if any(c for c in word if c.isalpha()):\n", " text += (word + \" \") * int(count)\n", "\n", " # predict the class\n", " X_test = vectorizer.transform([text])\n", " metadata['prediction'][tarinfo.name[0:-4]] = clf.decision_function(X_test)[0]\n", "\n", " tar.close()\n", " metadatas[genre] = metadata.sort('prediction', ascending=False)\n", " break\n", " return metadatas" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 101 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we should be ready to use our classifier on the HTRC Genre corpus. This returns a dictionary object with keys for each genre (fiction, drama, poetry) and values that are pandas dataframes with all the existing metadata for each volume, plus the philosophical prediction that we've added." ] }, { "cell_type": "code", "collapsed": false, "input": [ "htrc_genre_dir = \"/Users/sgs/Downloads/genre\"\n", "philo_metadatas = get_genre_metadata_and_predictions(htrc_genre_dir, philo_clf, stopword_vectorizer)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 100 }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can have a quick peek to see how many volumes are contained in each genre:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "total = 0\n", "for genre, metadata in philo_metadatas.items():\n", " total += len(metadata.index)\n", " print(genre+\": \"+\"{:,}\".format(len(metadata.index)))\n", "print(\"total: \"+\"{:,}\".format(total))\n" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "fiction: 101,948\n", "drama: 17,709\n", "poetry: 58,724\n", "total: 178,381\n" ] } ], "prompt_number": 190 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Listing Most Philosophical Texts" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Ok, so let's rub our hands together in anticipation and have a closer look at the predictions. For each genre, let's enumerate the 15 most philosophical texts (i.e. the texts that were assigned the highest values by our philosophical classifier)." ] }, { "cell_type": "code", "collapsed": false, "input": [ "for genre, metadata in philo_metadatas.items():\n", " print(genre)\n", " for name, row in metadata.head(15).iterrows():\n", " print(\" \"+str(row['prediction']) + \": \" + str(row[\"author\"]) + \" \" + str(row[\"title\"])[:40] + \" (\"+ name+\")\")" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "fiction\n", " 0.942876776127685: Hamilton, William, Lectures on metaphysics and logic (uc2.ark+=13960=t6d21t16h)\n", " 0.9264089941279002: Hamilton, William, Lectures on metaphysics and logic (uc2.ark+=13960=t5x63ch8w)\n", " 0.7556690393458386: Hamilton, William, Lectures on metaphysics and logic (uc2.ark+=13960=t3707z04z)\n", " 0.7400285535717109: Alcott, Amos Bronson, Table-talk (mdp.39015063976719)\n", " 0.7343142773526233: Ladd, George Trumbull, Primer of psychology (nyp.33433070247659)\n", " 0.7240166966930507: Morley, John, Critical miscellanies (uva.x002075999)\n", " 0.7224443869202736: Morley, John, Critical miscellanies (uc1.b3312082)\n", " 0.7221550252376431: Morley, John, Critical miscellanies (mdp.39015008447859)\n", " 0.7219327902034643: Morley, John, Critical miscellanies (uc1.b3271511)\n", " 0.7205189779025428: Morley, John, Critical miscellanies (uc2.ark+=13960=t9z03906q)\n", " 0.6752848002922364: Smith, Garnet, The melancholy of Stephen Allard (nyp.33433074925573)\n", " 0.6685784667208577: Dillon, Henry Augustus Dillon-Lee, The life and opinions of Sir Richard Mal (wu.89099782401)\n", " 0.6676523527212904: Greg, William R. Enigmas of life (uc1.b293840)\n", " 0.656211764437482: Lovett, Robert Morss, A wing\u00e9d victory (mdp.39015063939238)\n", " 0.6559990109761032: Mackintosh, James, The miscellaneous works of the Right Hon (mdp.39015011444083)\n", "drama\n", " 0.46788088291335583: Jones, Lloyd, A reply to Mr. R. Carlile's objections t (wu.89097121669)\n", " 0.10232714349406424: Muilman, Teresia Constantia, A letter humbly address'd to the Right H (mdp.39015035813768)\n", " 0.06650988674725727: nan Boston medical police (hvd.hxj8ev)\n", " 0.06509884255367532: Cleveland, Grover, Speech of Grover Cleveland, president of (njp.32101067015907)\n", " 0.054464962463584565: Combe, William, A letter to Her Grace the Duchess of Dev (mdp.39015073305511)\n", " 0.04846397981574457: nan An address to the people of Maine from t (nyp.33433034030118)\n", " 0.02053164585346362: Lessing, Gotthold Ephraim, Nathan the wise (uc2.ark+=13960=t0sq8qm0z)\n", " 0.0: Jones, Henry Arthur, Judah; (nyp.33433074928197)\n", " 0.0: Euripides. The tragedies of Euripides in English ve (nyp.33433082192612)\n", " 0.0: Euripides. The tragedies of Euripides in English ve (nyp.33433082192604)\n", " 0.0: Shakespeare, William, Much ado about nothing (nyp.33433075793939)\n", " 0.0: Shakespeare, William, The works of William Shakespeare (uva.x000031590)\n", " 0.0: Davidson, John, Plays (nyp.33433074912506)\n", " 0.0: Steele, Richard, Richard Steele (nyp.33433074912175)\n", " 0.0: Shakespeare, William, The complete works of Shakespeare (nyp.33433074892237)\n", "poetry\n", " 0.6253940555248959: Greenlaw, Asbury Lincoln, Resident forces of life, the evolution o (loc.ark+=13960=t4qj82h6d)\n", " 0.6236786508373916: Greenlaw, Asbury Lincoln, Resident forces of life, the evolution o (nyp.33433075833206)\n", " 0.540108435156661: Spalding, John Lancaster, The Spalding year-book; (mdp.39015064337135)\n", " 0.5400371868572602: Newcomb, Charles Benjamin, Principles of psychic philosophy (njp.32101066127778)\n", " 0.46935127211324157: Laidlaw, James S. God in reason and intuition (loc.ark+=13960=t3126bv3p)\n", " 0.4415951471487116: Gilmour, William Pegram, A diagnosis (uc2.ark+=13960=t2b853s2m)\n", " 0.43340354399532943: Gilmour, William Pegram, A diagnosis (loc.ark+=13960=t3vt29v3s)\n", " 0.4215994505874262: White, William Allen, A theory of spiritual progress; (uc2.ark+=13960=t46q1vf0j)\n", " 0.4171965056415603: Boyd, Jackson, The unveiling; (uc2.ark+=13960=t80k2b290)\n", " 0.41382667807742624: White, William Allen, A theory of spiritual progress; (nyp.33433081958526)\n", " 0.40420893766678634: Parsons, A. R. Surf lines that mark where waves of thou (loc.ark+=13960=t2988t00v)\n", " 0.39825467176157203: nan Surf lines that mark where waves of thou (uc2.ark+=13960=t5n873j3b)\n", " 0.3966047587208943: nan Surf lines that mark where waves of thou (nyp.33433074826847)\n", " 0.3899518109492506: De Waters, Lillian (Stephenson), Good cheer (loc.ark+=13960=t85h86d32)\n", " 0.38421283612256785: Blavatsky, H. P. Quotations (uc2.ark+=13960=t23b66b8t)\n" ] } ], "prompt_number": 171 }, { "cell_type": "markdown", "metadata": {}, "source": [ "One of the things this exposes immediately is that the HTRC genre feature sets contain duplicate texts (presumably because of sampling from different libraries \u2013\u00a0these aren't identifical files since they're the product of separated digitization and possibly separate editions). This is an annoyance, though we can probably just skip through duplicates in looking at the top samples from each group.\n", "\n", "Another noticeable thing is the set of 0.0 scores with drama. That score is likely because no prediction was made for the particular text, for some reason. But more importantly, it means that we don't dig very deep in the drama corpus before reaching texts that have negative scores (or zero), which means that the corpus as a whole appears to be less philosohpical. " ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Plotting by Year" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Because our volumes metadata contains date/year values, we can plot the philosophical predictions by year for each genre, this might give us a sense of some diachronic trends, how things change over time." ] }, { "cell_type": "code", "collapsed": false, "input": [ "import matplotlib.pyplot as plt\n", "%matplotlib inline \n", "\n", "for genre, metadata in philo_metadatas.items():\n", " metadata.plot(kind='scatter', x='date', y='prediction', label=genre)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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KZVs2edJZ4GxRITLOfTb19U0uu2xKT09Pxn72SdLiC2fmlpzv7OzM+nzs85vq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qLdwbHALec5i6SsCbTy6caGqiyaz8J5vC4mjGcTh32/y0FhcaLJ3QtjE+bqTD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REo2OTmv12xWQcK6rq2cZ68BuRVtTU+vLPelpn/iun+nyYrZcvCX1SZhrKK6G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"text": [ "" ] } ], "prompt_number": 170 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The clearest thing from these graphs is that all three genres show more variability over time. This is no doubt in part because there are more texts per year as we move forward in time, but that doesn't fully explain the larger discrepencies in scores \u2013 it would see that some texts are getting more philosophical while some texts are getting less philosohpical.\n", "\n", "We also see here a confirmation of our observation earlier about drama being less philosophical, we can eyeball that most scores are under zero. We can observe a crevasse around 1900 in drama, and an even more pronounced gap in poetery at about the same time. This may be caused by an issue with the [HTRC genre feature sets](https://sharc.hathitrust.org/genre) where poetry_1894-1899.tar.gz and drama_1880-1884.tar.gz are empty." ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Plotting Means by Year" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Plotting all 178,381 points makes for very dense scatterplots. Another way to look at change over time is to consider the annual mean philosophical value for each genre. In other words, we look at the average of all the classifier predictions by year, and then comapre by genre." ] }, { "cell_type": "code", "collapsed": false, "input": [ "plt.figure(figsize=(10,5))\n", "for genre, metadata in philo_metadatas.items():\n", " values = {}\n", " for key, grp in metadata.groupby(['date']):\n", " values[key] = grp['prediction'].mean()\n", " plt.plot(list(values.keys()), list(values.values()), label=genre)\n", "plt.legend(philo_metadatas.keys())\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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0EHzta9mfy+WITXaxfqE1YlaTdeKzJhMCbAwhlowmBwagqwu6u3MPzuNhcWQH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+rDM2odHaLFw89/Lrq6/vCHIrDl9Yqp4BMmiE6uQ1FaCkBvqSB9JSWCF8rLg0TsxhtFZv6lpsWM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\nKXTFaN2aJ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"text": [ "" ] } ], "prompt_number": 168 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The first century or so shows more fluctuation erratic than the rest (possibly because there are fewer texts sampled). We see the same weirdness (though even clearer here) with drama and poetry that we noticed in the previous plots. Most genres have a graduate drop in philosophically classified texts, with the possible exception of drama." ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Summary and Next Steps" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Even though our philosophical classifier was created with a relatively small and heterogeneous corpus, it seems useful in trying to identify philosophical texts in the HTRC Genre corpus, as well as suggesting some possible insights about genre and changes over time. In particular:\n", "\n", "* the HTRC Genre corpus has a lot of duplicate texts\n", "* the HTRC Genre corpus increases the number of volumes per year over time\n", "* there's an issue with the HTRC Genre corpus around the end of the 19th century\n", "* philosophical variation seems to increase over time\n", "* drama is the least philosohpical genre\n", "* fiction and poetry seem to get less philosophical over time\n", "\n", "It might be interesting to run the same experiment with the [LitCrit classifier](ClassifyingLitCrit.ipynb).\n", "\n", "The HTRC Genre corpus is a wonderful resource because it provides well-organized and readily-accessible word frequency values. The next step might be to try something similar on the full HTRC corpus of 4.8 volumes (though likely a subset of that since our classifier has been trained for English texts only)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "\n", "(CC-BY) By St\u00e9fan Sinclair, Geoffrey Rockwell and the [Trace of Theory team](https://github.com/htrc/ACS-TT), last updated November 16, 2015." ] } ], "metadata": {} } ] }