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
- Tweets, Trends and Retweet Visualizations
- Tweets, Trends and Retweet Visualizations Part 2
- Friends, Followers and Setwise Operations
- Friends, Followers and Setwise Operations Part 2
- Friends, Followers and Setwise Operations Part 3
- The Tweet, The Whole Tweet and Nothing but The Tweet
- The Tweet, The Whole Tweet and Nothing but The Tweet Part 2
- Bonus Material: #JustinBieber vs #TeaParty
- Title: Matthew Russell on Mining the Social Web
- Release date: January 2011
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 0636920018292
You might also like
Mining the Social Web - Google+
Google+ is a social media platform that allows its users to create profile pages and submit …
Mining the Social Web - Facebook
Are you interested in exploring the data generated by Facebook's over 1.28 billion daily active users? …
How Market Share Is Changing Around the World
Emerging markets are catching up - and then some.
Spotlight on Learning from Failure: Creating Better Data Pipelines with Natalino Busa
When considering the complexities of implementing a next-generation data pipeline, the risk of over-promising and under-delivering …