Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Instagram, GitHub, and More - Matthew A. Russell
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
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Format : epub
Size: 7.4 Mb
ISBN : 9781491985045
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9/14/19, 8:44 AM
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