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MINING THE SOCIAL WEB
Título:
MINING THE SOCIAL WEB
Subtítulo:
Autor:
MATTHEW A. RUSSELL; MIKHAIL KLASSEN
Editorial:
Oreilly & Associates Inc
Año de edición:
2019
ISBN:
978-1-4919-8504-5
Páginas:
400
disponibilidad:
NO DISPONIBLE PREGUNTAR POR EMAIL TIEMPO
Colección:
< Genérica >
56,00 € Comprar

Sinopsis

u003cpu003eMine 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.u003c/pu003e u003cpu003eIn 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.u003c/pu003e u003culu003e u003cliu003eGet a straightforward synopsis of the social web landscapeu003c/liu003e u003cliu003eUse Docker to easily run each chapter's example code, packaged as a Jupyter notebooku003c/liu003e u003cliu003eAdapt and contribute to the code's open source GitHub repositoryu003c/liu003e u003cliu003eLearn how to employ best-in-class Python 3 tools to slice and dice the data you collectu003c/liu003e u003cliu003eApply advanced mining techniques such as TFIDF, cosine similarity, collocation analysis, clique detection, and image recognitionu003c/liu003e u003cliu003eBuild beautiful data visualizations with Python and JavaScript toolkitsu003c/liu003e u003c/ulu003e