Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More

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9781449367619: Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More

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 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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Book Description:

Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More

About the Author:

Matthew Russell, Chief Technology Officer at Digital Reasoning, Principal at Zaffra, and author of several books on technology including Mining the Social Web (O'Reilly, 2013), now in its second edition. He is passionate about open source software development, data mining, and creating technology to amplify human intelligence. Matthew studied computer science and jumped out of airplanes at the United States Air Force Academy. When not solving hard problems, he enjoys practicing Bikram Hot Yoga, CrossFitting and participating in triathlons.

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Descripción O Reilly Media, Inc, USA, United States, 2013. Paperback. Estado de conservación: New. 2nd Revised edition. Language: English . Brand New Book. 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. Nº de ref. de la librería AAH9781449367619

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Descripción O Reilly Media, Inc, USA, United States, 2013. Paperback. Estado de conservación: New. 2nd Revised edition. Language: English . Brand New Book. 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. Nº de ref. de la librería AAH9781449367619

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