21 Recipes for Mining Twitter de Matthew A Russell

21 Recipes for Mining Twitter

Matthew A Russell

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.

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Cuprins

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);