How can you tap into the wealth of social web data to discover whoâs making connections with whom, what theyâre talking about, and where theyâre located? With this expanded and thoroughly revised edition, youâll 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
- Take advantage of more than two-dozen Twitter recipes, presented in OâReillyâs popular "problem/solution/discussion" cookbook format
The example code for this unique data science book is maintained in a public GitHub repository. Itâs 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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