"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 O Reilly's Mining the Social Web.

About The Author

Matthew Russell, Vice President of Engineering at Digital Reasoning Systems (http://www.digitalreasoning.com/) and Principal at Zaffra (http://zaffra.com), is a computer scientist who is passionate about data mining, open source, and web application technologies. He s also the author of Dojo: The Definitive Guide (O Reilly).

Table of Content

Chapter 1 The Recipes



Using OAuth to Access Twitter APIs
Looking Up the Trending Topics
Extracting Tweet Entities
Searching for Tweets
Extracting a Retweet s Origins
Creating a Graph of Retweet Relationships
Visualizing a Graph of Retweet Relationships
Capturing Tweets in Real-time with the Streaming API
Making Robust Twitter Requests
Harvesting Tweets
Creating a Tag Cloud from Tweet Entities
Summarizing Link Targets
Harvesting Friends and Followers
Performing Setwise Operations on Friendship Data
Resolving User Profile Information
Crawling Followers to Approximate Potential Influence
Analyzing Friendship Relationships such as Friends of Friends
Analyzing Friendship Cliques
Analyzing the Authors of Tweets that Appear in Search Results
Visualizing Geodata with a Dorling Cartogram
Geocoding Locations from Profiles (or Elsewhere)"

To be updated