Mining the Social Web

    By

    How can you tap into the wealth of social web data to discover who's making connections with whom, what they're talking about, and where they're located? With this expanded and thoroughly revised edition, you'll learn how to acquire, analyze, and summarize data from all corners of the social web, including Facebook, Twitter, LinkedIn, Google+, GitHub, email, websites, and blogs. Employ IPython Notebook, the Natural Language Toolkit, NetworkX, and other scientific computing tools to mine popular social web sites Apply advanced text-mining techniques, such as clustering and TF-IDF, to extract meaning from human language data Bootstrap interest graphs from GitHub by discovering affinities among people, programming languages, and coding projects Build interactive visualizations with D3.js, an extraordinarily flexible HTML5 and JavaScript toolkit Take advantage of more than two-dozen Twitter recipes, presented in O'Reilly's popular "problem/solution/discussion" cookbook format The example code for this unique data science book is maintained in a public GitHub repository. It's designed to be easily accessible through a turnkey virtual machine that facilitates interactive learning with an easy-to-use collection of IPython Notebooks.

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    Number of Pages: 448
    Format(s): Paperback - ISBN: 9781449367619
    Publication Date:
    Listed in: Data mining
    Publisher: O'Reilly Media, Inc, USA

    Books by Matthew Russell

    Paperback

    RRP: £34.50

    Sale Price: £23.53

    Save: £10.97 per copy!

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