There is so much potential in extracting, processing and synthesizing the the multi faceted, realtime data that can be mined from social sites. Mining the Social Web by Mathew A. Rusell covers these topics scrupulously. Here is my detailed review of the book
Chapter 1: Mining Twitter, Exploring Trending topics, Discovering what users are talking about
This is an informative chapter which covers from the basics of how to create applications with Twitter, authorizing an application to access Twitter data, looking for trends, searching for tweets and how to extract the text, screen names and hashtags from the tweets. It also covers how to compute the lexical diversity of the tweets and visualizing the data with histograms. It covers matplotlib, prettytable and other Python packages. I have used Twitter APIs extensively and found this chapter very useful and well written.
Chapter 2 : Mining Facebook: Analyzing Fan Pages, Examining Friendships, and More
This chapter covers the developer tools for Facebook, Graph API explorer, using the API over HTTP, Open Graph Protocol, examining friendships and analyzing social graph connections. It demonstrates how to use facebook-sdk package to make FQL queries. Other examples include computing overlapping likes in social network, analyzing mutual friendships and visualizing with D3.js. This chapter makes it apparent that there are many exciting possibilities for what can be done with social data, and that there