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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 3. Users, Followers, and Communities on Twitter

This chapter continues the discussion on mining Twitter data. After focusing on the analysis of tweets in the previous chapter, we will now shift our attention to the users, their connections, and their interactions.

In this chapter, we will discuss the following topics:

How to download a list of friends and followers for a given user
How to analyze connections between users, mutual friends, and so on
How to measure influence and engagement on Twitter
Clustering algorithms and how to cluster users using scikit-learn
Network analysis and how to use it to mine conversations on Twitter
How to create dynamic maps to visualize the location of tweets

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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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