Synopses & Reviews
Millions of public Twitter streams harbor a wealth of data, and once you mine them, you can gain some valuable insights. This short and concise book offers a collection of recipes to help you extract nuggets of Twitter information using easy-to-learn Python tools. Each recipe offers a discussion of how and why the solution works, so you can quickly adapt it to fit your particular needs. The recipes include techniques to:
- Use OAuth to access Twitter data
- Create and analyze graphs of retweet relationships
- Use the streaming API to harvest tweets in realtime
- Harvest and analyze friends and followers
- Discover friendship cliques
- Summarize webpages from short URLs
This book is a perfect companion to OReilly's Mining the Social Web.
Synopsis
If you want to start working with the rich data stream that comes out of Twitter, here's how. 21 recipes to get you started. A great companion to Mining the Social Web.
About the Author
Matthew Russell, Chief Technology Officer at Digital Reasoning, Principal at Zaffra, and author of several books on technology including Mining the Social Web (O'Reilly, 2013), now in its second edition. He is passionate about open source software development, data mining, and creating technology to amplify human intelligence. Matthew studied computer science and jumped out of airplanes at the United States Air Force Academy. When not solving hard problems, he enjoys practicing Bikram Hot Yoga, CrossFitting and participating in triathlons.
Table of Contents
Preface; Introduction; Conventions Used in This Book; Using Code Examples; Safari® Books Online; How to Contact Us; Chapter 1: The Recipes; 1.1 Using OAuth to Access Twitter APIs; 1.2 Looking Up the Trending Topics; 1.3 Extracting Tweet Entities; 1.4 Searching for Tweets; 1.5 Extracting a Retweet's Origins; 1.6 Creating a Graph of Retweet Relationships; 1.7 Visualizing a Graph of Retweet Relationships; 1.8 Capturing Tweets in Real-time with the Streaming API; 1.9 Making Robust Twitter Requests; 1.10 Harvesting Tweets; 1.11 Creating a Tag Cloud from Tweet Entities; 1.12 Summarizing Link Targets; 1.13 Harvesting Friends and Followers; 1.14 Performing Setwise Operations on Friendship Data; 1.15 Resolving User Profile Information; 1.16 Crawling Followers to Approximate Potential Influence; 1.17 Analyzing Friendship Relationships such as Friends of Friends; 1.18 Analyzing Friendship Cliques; 1.19 Analyzing the Authors of Tweets that Appear in Search Results; 1.20 Visualizing Geodata with a Dorling Cartogram; 1.21 Geocoding Locations from Profiles (or Elsewhere);