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Título: MINING THE SOCIAL WEB. DATA MINING FACEBOOK, TWITTER, LINKEDIN, INSTAGRAM, GITHUB, AND MORE. 3rd Edition
Autor: RUSSELL, MATTHEW A. & KLASSEN, MIKHAIL
Año: 2019
Género: CIENCIAS COMPUTACIONALES Y TECNOLOGÍAS DE INFORMACIÓN
Formato: PDF

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», 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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