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Mining the social web

By: Russell, Matthew A
Title By: Klassen, Mikhail
Material type: BookPublisher: Beijing : O'Reilly, c2019.Edition: 3rd ed.Description: xxiv, 400 p. : ill. ; 24 cm.ISBN: 9781491985045Other title: Data mining Facebook, Twitter, LinkedIn, Instagram, GitHub, and more.Subject(s): Data mining | Online social networksDDC classification: 006.312 RU MI Online resources: Location Map
Summary:
"Mine the rich data tucked away in popular social websites like Twitter, Facebook, LinkedIn, Instagram, and GitHub. With the third edition of this popular guide, data scientists, analysts,and programmers will learn how to glean insights from social media--who's connecting with whom, what they're talking about, and where they're located--using Python code examples, Jupyter notebooks, or Docker containers."--Back cover.
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Item type Home library Call number Status Notes Date due Barcode Item holds
REGULAR University of Wollongong in Dubai
Main Collection
006.312 RU MI (Browse shelf) Available March2019 T0061917
Total holds: 0

"Revision history for the third edition"--Title page verso.

Includes bibliographical references and index.

Mining Twitter: exploring trending topics, discovering what people are talking about, and more -- Mining Facebook: analyzing fan pages, examining friendships, and more -- Mining Instagram: computer vision, neural networks, object recognition, and face detection -- Mining LinkedIn: faceting job titles, clustering colleagues, and more -- Mining text files: computing document similarity, extracting collocations, and more -- Mining web pages: using natural language processing to understand human language, summarize blog posts, and more -- Mining mailboxes: analyzing who's talking to whom about what, how often, and more -- Mining GitHub: inspecting software collaboration habits, building interest graphs, and more -- Twitter cookbook -- Appendixes.

"Mine the rich data tucked away in popular social websites like Twitter, Facebook, LinkedIn, Instagram, and GitHub. With the third edition of this popular guide, data scientists, analysts,and programmers will learn how to glean insights from social media--who's connecting with whom, what they're talking about, and where they're located--using Python code examples, Jupyter notebooks, or Docker containers."--Back cover.

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