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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 4. Posts, Pages, and User Interactions on Facebook

In a book about social media mining, the reader probably expects a chapter about Facebook. Launched in 2004, and initially limited to Harvard students, today Facebook is a multi-billion dollar company with nearly 1.5 billion monthly active users. Its popularity makes it an extremely interesting playground for data mining.

In this chapter, we will discuss the following topics:

Creating an app to interact with the Facebook platform
Interacting with the Facebook Graph API
Mining posts from the authenticated user
Mining Facebook Pages, visualizing posts, and measuring engagement
Building a word cloud from a set of posts

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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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