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Mastering Social Media Mining with Python

You're reading from Mastering Social Media Mining with Python Unearth deeper insight from your social media data with advanced Python techniques for acquisition and analysis

Product type Paperback

Published in Jul 2016

Publisher Packt

ISBN-13 9781783552016

Length 338 pages

Edition 1st Edition

Languages

Python

Concepts

Data Mining

Author (1):

Marco Bonzanini

View More author details

Table of Contents (10) Chapters

Preface

1. Social Media, Social Data, and Python FREE CHAPTER

2. #MiningTwitter – Hashtags, Topics, and Time Series

3. Users, Followers, and Communities on Twitter

4. Posts, Pages, and User Interactions on Facebook

5. Topic Analysis on Google+

6. Questions and Answers on Stack Exchange

7. Blogs, RSS, Wikipedia, and Natural Language Processing

8. Mining All the Data!

9. Linked Data and the Semantic Web

Chapter 7. Blogs, RSS, Wikipedia, and Natural Language Processing

This chapter focuses on natural language processing (NLP), the field of study that deals with natural language. Before digging into the details of NLP, we'll analyze some options to download textual data from the Web.

In this chapter, we will discuss the following topics:

How to interact with the WordPress.com and Blogger APIs
Web feed formats (RSS and Atom) and their use
How to store data from blogs in the JSON format
How to interact with the Wikipedia API to search the information about entities
The core notions of NLP, particularly with regard to text preprocessing
How to process textual data to identify entities mentioned in the text

The rest of the chapter is locked

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Authors (1)

Bonzanini

Bonzanini

Marco Bonzanini is a data scientist based in London, United Kingdom. He holds a Ph.D. in information retrieval from the Queen Mary University of London. He specializes in text analytics and search applications, and over the years, he has enjoyed working on a variety of information management and data science problems. He maintains a personal blog at https://marcobonzanini.com, where he discusses different technical topics, mainly around Python, text analytics, and data science. When not working on Python projects, he likes to engage with the community at PyData conferences and meetups, and he also enjoys brewing homemade beer.

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