Name:	Text Mining Project
Author:	Sparsh Bansal
Version:	3.0

Text Mining is a project in Software Design at Olin College of Engineering. It conducts the following analyses on a given text:

i:	Pickles the books from a given web link
ii:	Analysis 1 - Word Frequency Analysis
iii:	Analysis 2 - Markov Analysis
iv:	Analysis 3 - Sentiment Analysis

Requirements

Text Mining Version 3.0 requires the following Python packages

import pickle
import requests
import string
from string import punctuation
from string import whitespace
from bs4 import BeautifulSoup
import re
import sys
import random
import numpy as np
from nltk.sentiment.vader import SentimentIntensityAnalyzer

Installation

The easiest and fastest way to get the packages up and running:

import requests
print(requests.get('http://google.com').text)
python -m nltk.downloader all

Documentation

I have added comments for every line of code that I felt could be beneficial for someone to understand the program

Note: I haved added comments especially on the imported packages and code so that I can fully understand the code written by someone else. I have cited the sources wherever appropriate.

Contributing

I used information from:

i:	Think Python - Allen Downey
i:	Vader - NLTK Corpora

Citing

Hutto, C.J. & Gilbert, E.E. (2014). VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text. Eighth International Conference on Weblogs and Social Media (ICWSM-14). Ann Arbor, MI, June 2014

https://www.greenteapress.com/thinkpython/thinkpython.pdf