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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

Mining Facebook Pages

Facebook is not only used by individuals who want to connect with their friends and relatives, but also by companies, brands, and organizations who want to engage with people. A Facebook Page is created and managed by a Facebook personal account, and it can be used in a variety of ways:

To share information about a business (for example, a restaurant or online shop)
To represent a celebrity (for example, a footballer or rock band)
To connect with an audience (for example, as an extension of an online community)

Different from personal accounts, Pages can publish posts that are publicly visible. Regular users can like a Page, meaning that they'll receive the content updates published by the Page directly on their news feed, that is, their personalized Facebook home page.

For example, Packt Publishing's Facebook Page is located at https://www.facebook.com/PacktPub and it contains general information about PacktPub, as well as the posts related to books, e-books...

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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