Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Instagram, GitHub, and More (3)

By: Matthew A. Russell and Mikhail Klassen

Sign Up Now! Already a Member? Log In
You must be logged into Bookshare to access this title. Learn about membership options, or view our freely available titles.

Synopsis: Mine the rich data tucked away in popular social websites such as Twitter, Facebook, LinkedIn, and Instagram. With the third edition of this popular guide, data scientists, analysts, and programmers will learn how to glean insights from social media—including who’s connecting with whom, what they’re talking about, and where they’re located—using Python code examples, Jupyter notebooks, or Docker containers.In part one, each standalone chapter focuses on one aspect of the social landscape, including each of the major social sites, as well as web pages, blogs and feeds, mailboxes, GitHub, and a newly added chapter covering Instagram. Part two provides a cookbook with two dozen bite-size recipes for solving particular issues with Twitter.Get a straightforward synopsis of the social web landscapeUse Docker to easily run each chapter’s example code, packaged as a Jupyter notebookAdapt and contribute to the code’s open source GitHub repositoryLearn how to employ best-in-class Python 3 tools to slice and dice the data you collectApply advanced mining techniques such as TFIDF, cosine similarity, collocation analysis, clique detection, and image recognitionBuild beautiful data visualizations with Python and JavaScript toolkits