Specifications
| book-author | Matthew Russell, Mikhail Klassen |
|---|---|
| publisher | O’Reilly Media; 3rd edition |
| file-type | EPUB |
| pages | 432 pages |
| language | English |
| asin | B07L46FZ8Y |
| isbn10 | 1491985046 |
| isbn13 | 9781491985045 |
Book Description
Mine the rich data tucked away in popular social websites such as Facebook; Twitter; Instagram and LinkedIn. With the 3rd edition of this popular guide “Mining the Social Web: Data Mining Facebook; Twitter; LinkedIn; Instagram; GitHub; and More 3rd edition” analysts; data scientists; and programmers will learn how to glean insights from social media — including who’s connecting with whom; what they are talking about; and where they are located — using Jupyter notebooks; Python code examples; or Docker containers.
In part 1; each standalone chapter focuses on one aspect of the social landscape; including each of the major social sites; as well as blogs; web pages and feeds; GitHub; mailboxes; and a newly added chapter covering Instagram. Part 2 provides a cookbook with 2 dozen bite-size recipes for solving particular issues with Twitter.
- Get a straightforward synopsis of the social web landscape
- Adapt and contribute to the code’s open source GitHub repository
- Build beautiful data visualizations with Python and JavaScript toolkits
- Learn how to employ best-in-class Python 3 tools to slice and dice the data you collect
- Use Docker to easily run each chapter’s example code; packaged as a Jupyter notebook
- Apply advanced mining techniques such as cosine similarity; TFIDF; collocation analysis; clique detection; and image recognition
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