
Mining the Social Web (Sách keo gáy, bìa mềm)
Categories:Mathematics - Mathematical Statistics
Year:2019
Edition:3
Language:english
Pages:423
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 landscape Use Docker to
easily run each chapter's example code, packaged as a Jupyter notebook
Adapt and contribute to the code's open source GitHub repository Learn
how to employ best-in-class Python 3 tools to slice and dice the data
you collect Apply advanced mining techniques such as TFIDF, cosine
similarity, collocation analysis, clique detection, and image
recognition Build beautiful data visualizations with Python and
JavaScript toolkits
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