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Python: End-to-end Data Analysis

You're reading from   Python: End-to-end Data Analysis Leverage the power of Python to clean, scrape, analyze, and visualize your data

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Product type Course
Published in May 2017
Publisher Packt
ISBN-13 9781788394697
Length 931 pages
Edition 1st Edition
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Authors (5):
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Luiz Felipe Martins Luiz Felipe Martins
Author Profile Icon Luiz Felipe Martins
Luiz Felipe Martins
Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
Phuong Vo.T.H Phuong Vo.T.H
Author Profile Icon Phuong Vo.T.H
Phuong Vo.T.H
Martin Czygan Martin Czygan
Author Profile Icon Martin Czygan
Martin Czygan
Magnus Vilhelm Persson Magnus Vilhelm Persson
Author Profile Icon Magnus Vilhelm Persson
Magnus Vilhelm Persson
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Toc

Chapter 8. Text Mining and Social Network Analysis

In this chapter, we will cover the following recipes:

  • Creating a categorized corpus
  • Tokenizing news articles in sentences and words
  • Stemming, lemmatizing, filtering, and TF-IDF scores
  • Recognizing named entities
  • Extracting topics with non-negative matrix factorization
  • Implementing a basic terms database
  • Computing social network density
  • Calculating social network closeness centrality
  • Determining the betweenness centrality
  • Estimating the average clustering coefficient
  • Calculating the assortativity coefficient of a graph
  • Getting the clique number of a graph
  • Creating a document graph with cosine similarity

Introduction

Humans have communicated through language for thousands of years. Handwritten texts have been around for ages, the Gutenberg press was of course a huge development, but now that we have computers, the Internet, and social media, things have definitely spiraled out of control.

This chapter will help you cope with the flood of textual...

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