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+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Written text as operational data\n",
+ "\n",
+ "Written text is one type of data\n",
+ "\n",
+ "### Why people write?\n",
+ "\n",
+ " - To communicate: their thoughts, feelings, urgency, needs, information\n",
+ "\n",
+ "### Why people communicate?\n",
+ "\n",
+ "1. To express emotions\n",
+ "1. To share information\n",
+ "1. To enable or elicit an action\n",
+ "1. ...\n",
+ "\n",
+ "### We will use written text for the purpose other than \n",
+ "1. To experience emotion\n",
+ "1. To learn something the author intended us to learn\n",
+ "1. To do what the author intended us to do\n",
+ "\n",
+ "### Instead, we will use written text to recognize who wrote it\n",
+ " - By calculating and comparing word frequencies in written documents\n",
+ " \n",
+ "See, for example, likely fictional story https://medium.com/@amuse/how-the-nsa-caught-satoshi-nakamoto-868affcef595"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Example 1. Dictionaries in python (associative arrays)\n",
+ "\n",
+ "Plot the frequency distribution of words on a web page."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "\t1\n",
+ "
\t1\n",
+ "403\t1\n",
+ "Forbidden \t1\n",
+ "\t1\n",
+ "Forbidden \t1\n",
+ "You\t1\n",
+ "don't\t1\n",
+ "have\t1\n",
+ "permission\t1\n",
+ "to\t1\n"
+ ]
+ }
+ ],
+ "source": [
+ "import requests, re\n",
+ "# re is a module for regular expressions: to detect various combinations of characters\n",
+ "import operator\n",
+ "\n",
+ "# Start from a simple document\n",
+ "r = requests .get('http://eecs.utk.edu')\n",
+ "\n",
+ "# What comes back includes headers and other HTTP stuff, get just the body of the response\n",
+ "t = r.text\n",
+ "\n",
+ "# obtain words by splitting a string using as separator one or more (+) space/like characters (\\s) \n",
+ "wds = re.split('\\s+',t)\n",
+ "\n",
+ "# now populate a dictionary (wf)\n",
+ "wf = {}\n",
+ "for w in wds:\n",
+ " if w in wf: wf [w] = wf [w] + 1\n",
+ " else: wf[w] = 1\n",
+ "\n",
+ "# dictionaries can not be sorted, so lets get a sorted *list* \n",
+ "wfs = sorted (wf .items(), key = operator .itemgetter (1), reverse=True) \n",
+ "\n",
+ "# lets just have no more than 15 words \n",
+ "ml = min(len(wfs),15)\n",
+ "for i in range(1,ml,1):\n",
+ " print (wfs[i][0]+\"\\t\"+str(wfs[i][1])) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Example 2\n",
+ "\n",
+ "Lots of markup in the output, lets remove it --- \n",
+ "\n",
+ "use BeautifulSoup and nltk modules and practice some regular expressions."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import requests, re, nltk\n",
+ "from bs4 import BeautifulSoup\n",
+ "from nltk import clean_html\n",
+ "from collections import Counter\n",
+ "import operator\n",
+ "\n",
+ "# we may not care about the usage of stop words\n",
+ "stop_words = nltk.corpus.stopwords.words('english') + [\n",
+ " 'ut', '\\'re','.', ',', '--', '\\'s', '?', ')', '(', ':', '\\'',\n",
+ " '\\\"', '-', '}', '{', '&', '|', u'\\u2014' ]\n",
+ "\n",
+ "# We most likely would like to remove html markup\n",
+ "def cleanHtml (html):\n",
+ " from bs4 import BeautifulSoup\n",
+ " soup = BeautifulSoup(html, 'html.parser')\n",
+ " return soup .get_text()\n",
+ "\n",
+ "# We also want to remove special characters, quotes, etc. from each word\n",
+ "def cleanWord (w):\n",
+ " # r in r'[.,\"\\']' tells to treat \\ as a regular character \n",
+ " # but we need to escape ' with \\'\n",
+ " # any character between the brackets [] is to be removed \n",
+ " wn = re.sub('[,\"\\.\\'&\\|:@>*;/=]', \"\", w)\n",
+ " # get rid of numbers\n",
+ " return re.sub('^[0-9\\.]*$', \"\", wn)\n",
+ " \n",
+ "# define a function to get text/clean/calculate frequency\n",
+ "def get_wf (URL):\n",
+ " # first get the web page\n",
+ " r = requests .get(URL)\n",
+ " \n",
+ " # Now clean\n",
+ " # remove html markup\n",
+ " t = cleanHtml (r .text) .lower()\n",
+ " \n",
+ " # split string into an array of words using any sequence of spaces \"\\s+\" \n",
+ " wds = re .split('\\s+',t)\n",
+ " \n",
+ " # remove periods, commas, etc stuck to the edges of words\n",
+ " for i in range(len(wds)):\n",
+ " wds [i] = cleanWord (wds [i])\n",
+ " \n",
+ " # If satisfied with results, lets go to the next step: calculate frequencies\n",
+ " # We can write a loop to create a dictionary, but \n",
+ " # there is a special function for everything in python\n",
+ " # in particular for counting frequencies (like function table() in R)\n",
+ " wf = Counter (wds)\n",
+ " \n",
+ " # Remove stop words from the dictionary wf\n",
+ " for k in stop_words:\n",
+ " wf. pop(k, None)\n",
+ " \n",
+ " #how many regular words in the document?\n",
+ " tw = 0\n",
+ " for w in wf:\n",
+ " tw += wf[w] \n",
+ " \n",
+ " \n",
+ " # Get ordered list\n",
+ " wfs = sorted (wf .items(), key = operator.itemgetter(1), reverse=True)\n",
+ " ml = min(len(wfs),15)\n",
+ "\n",
+ " #Reverse the list because barh plots items from the bottom\n",
+ " return (wfs [ 0:ml ] [::-1], tw)\n",
+ " \n",
+ "# Now populate two lists \n",
+ "(wf_ee, tw_ee) = get_wf('http://www.gutenberg.org/ebooks/1342.txt.utf-8')\n",
+ "(wf_bu, tw_bu) = get_wf('http://www.gutenberg.org/ebooks/76.txt.utf-8')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#Plot the results: are there striking differences in language?\n",
+ "import numpy as np\n",
+ "import pylab\n",
+ "import matplotlib.pyplot as plt\n",
+ "\n",
+ "%matplotlib inline\n",
+ "def plotTwoLists (wf_ee, wf_bu, title):\n",
+ " f = plt.figure (figsize=(10, 6))\n",
+ " # this is painfully tedious....\n",
+ " f .suptitle (title, fontsize=20)\n",
+ " ax = f.add_subplot(111)\n",
+ " ax .spines ['top'] .set_color ('none')\n",
+ " ax .spines ['bottom'] .set_color ('none')\n",
+ " ax .spines ['left'] .set_color ('none')\n",
+ " ax .spines ['right'] .set_color ('none')\n",
+ " ax .tick_params (labelcolor='w', top='off', bottom='off', left='off', right='off', labelsize=20)\n",
+ "\n",
+ " # Create two subplots, this is the first one\n",
+ " ax1 = f .add_subplot (121)\n",
+ " plt .subplots_adjust (wspace=.5)\n",
+ "\n",
+ " pos = np .arange (len(wf_ee)) \n",
+ " ax1 .tick_params (axis='both', which='major', labelsize=14)\n",
+ " pylab .yticks (pos, [ x [0] for x in wf_ee ])\n",
+ " ax1 .barh (range(len(wf_ee)), [ x [1] for x in wf_ee ], align='center')\n",
+ "\n",
+ " ax2 = f .add_subplot (122)\n",
+ " ax2 .tick_params (axis='both', which='major', labelsize=14)\n",
+ " pos = np .arange (len(wf_bu)) \n",
+ " pylab .yticks (pos, [ x [0] for x in wf_bu ])\n",
+ " ax2 .barh (range (len(wf_bu)), [ x [1] for x in wf_bu ], align='center')\n",
+ "\n",
+ "plotTwoLists (wf_ee, wf_bu, 'Difference between Pride and Prejudice and Huck Finn')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "and\t2836\n",
+ "of\t2676\n",
+ "to\t2646\n",
+ "a\t2217\n",
+ "in\t1422\n",
+ "his\t1205\n",
+ "he\t928\n",
+ "that\t920\n",
+ "was\t823\n",
+ "for\t798\n",
+ "with\t797\n",
+ "as\t672\n",
+ "I\t505\n",
+ "you\t497\n"
+ ]
+ }
+ ],
+ "source": [
+ "#In case Project gutenberg is blocked you can download text to your laptop and copy to the docker container via scp\n",
+ "#Assuming the file name you copy is pg4680.txt here is how you change the script\n",
+ "# Please note the option errors='replace'\n",
+ "# without it python invariably runs into unicode errors\n",
+ "f = open ('pg4680.txt', 'r', encoding=\"ascii\", errors='replace')\n",
+ " \n",
+ "# What comes back includes headers and other HTTP stuff, get just the body of the response\n",
+ "t = f.read()\n",
+ "\n",
+ "# obtain words by splitting a string using as separator one or more (+) space/like characters (\\s) \n",
+ "wds = re.split('\\s+',t)\n",
+ "\n",
+ "# now populate a dictionary (wf)\n",
+ "wf = {}\n",
+ "for w in wds:\n",
+ " if w in wf: wf [w] = wf [w] + 1\n",
+ " else: wf [w] = 1\n",
+ "\n",
+ "# dictionaries can not be sorted, so lets get a sorted *list* \n",
+ "wfs = sorted (wf .items(), key = operator .itemgetter (1), reverse=True) \n",
+ "\n",
+ "# lets just have no more than 15 words \n",
+ "ml = min(len(wfs),15)\n",
+ "for i in range(1,ml,1):\n",
+ " print (wfs[i][0]+\"\\t\"+str(wfs[i][1])) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Assignment 1\n",
+ "\n",
+ "1. Compare word frequencies between two works of a single author.\n",
+ "1. Compare word frequencies between works of two authors.\n",
+ "1. Are there some words preferred by one author but used less frequently by another author?\n",
+ "\n",
+ "Extra credit\n",
+ "\n",
+ "1. The frequency of a specific word, e.g., \"would\" should follow a binomial distribution (each regular word in a document is a trial and with probability p that word is \"would\". The estimate for p is N(\"would\")/N(regular word)). Do these binomial distributions for your chosen word differ significantly between books of the same author or between authors? \n",
+ "\n",
+ "Project Gutenberg is a good source of for fiction and non-fiction.\n",
+ "\n",
+ "E.g below are two most popular books from Project Gutenberg:\n",
+ "- Pride and Prejudice at http://www.gutenberg.org/ebooks/1342.txt.utf-8\n",
+ "- Adventures of Huckleberry Finn at http://www.gutenberg.org/ebooks/76.txt.utf-8"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import requests, re, nltk\n",
+ "#In case your text is not on Project Gutenberg but at some other URL\n",
+ "#http://www.fullbooks.com/Our-World-or-The-Slaveholders-Daughter2.html\n",
+ "# that contains 12 parts\n",
+ "t = \"\"\n",
+ "for i in range(2,13):\n",
+ " r = requests .get('http://www.fullbooks.com/Our-World-or-The-Slaveholders-Daughter' + str(i) + '.html')\n",
+ " t = t + r.text"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "1323653"
+ ]
+ },
+ "execution_count": 18,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "len(t)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 23,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/usr/local/lib/python3.8/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 128 (\\x80) missing from current font.\n",
+ " fig.canvas.print_figure(bytes_io, **kw)\n",
+ "/usr/local/lib/python3.8/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 147 (\\x93) missing from current font.\n",
+ " fig.canvas.print_figure(bytes_io, **kw)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#Compare word frequencies between two works of a single author.\n",
+ "(wf_HS, tw_HS) = get_wf('https://www.gutenberg.org/files/68980/68980-h/68980-h.htm')\n",
+ "(wf_AW, tw_AW) = get_wf('https://www.gutenberg.org/files/68979/68979-h/68979-h.htm')\n",
+ "plotTwoLists (wf_HS, wf_AW, \"Two books by Zsigmond Kemény\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 22,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#Compare word frequencies between works of two authors.\n",
+ "(wf_HS, tw_HS) = get_wf('https://www.gutenberg.org/files/345/345-h/345-h.htm')\n",
+ "(wf_AW, tw_AW) = get_wf('https://www.gutenberg.org/files/84/84-h/84-h.htm')\n",
+ "plotTwoLists (wf_HS, wf_AW, \"Two books: One by Bram Stoker and another by Mary Shelley\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The word \"said\" is used by Bram Stoker than Mary Shelley. One interesting thing is that dracula through out the story uses more words than the monstor frankenstein so that is why Bram Stoker uses that word more often."
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.8.10"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}