Twitter has become a lean, mean data-collecting machine, and with this entertaining video course, you'll learn techniques for mining this vast wealth of information. Follow along as author and data analyst Matthew Russell shows O'Reilly's Director of Market Research how easy it is to uncover valuable Twitter data with basic Python tools and pragmatic storage technologies such as Redis and CouchDB.
Matthew analyzes the Twitter stream of top-tweeter Tim O'Reilly, looks in-depth into a friendship network, and considers Freakonomic questions such as "What does Justin Bieber have in common with the Tea Party?" Based on portions of Matthew’s book, Mining the Social Web (O'Reilly, 2011), this fast-moving presentation is ideal for beginning to intermediate programmers, as well as data analysts, who want to find extraordinary nuggets of information in the Twitter data haystack.
Table of Contents
- Overview 00:13:43
- Tweets, Trends and Retweet Visualizations 00:12:40
- Tweets, Trends and Retweet Visualizations Part 2 00:25:07
- Friends, Followers and Setwise Operations 00:21:07
- Friends, Followers and Setwise Operations Part 2 00:32:43
- Friends, Followers and Setwise Operations Part 3 00:22:29
- The Tweet, The Whole Tweet and Nothing but The Tweet 00:22:39
- The Tweet, The Whole Tweet and Nothing but The Tweet Part 2 00:29:16
- Bonus Material: #JustinBieber vs #TeaParty 00:12:51
- Title: Matthew Russell on Mining the Social Web
- Release date: January 2011
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 0636920018292