Primeros reseñadoresMatthew A. Russell

Facebook, Twitter, LinkedIn, Google+, and other social web properties generate a wealth of valuable social data, but how can you tap into this data and discover who’s connecting with whom, which insights are lurking just beneath the surface, and what people are talking about? This ebook shows you how to answer these questions and many more. Each chapter combines popular and useful social web data with analysis techniques and visualization to help you find the needles in the social haystack that you've been looking for—as well as many you probably didn't even know existed. In this expanded and thoroughly revised second edition you’ll learn how to: Navigate the most popular social web APIs to access, collect, analyze, and visualize social web data Employ IPython Notebook and other easy to use Python packages such as the Natural Language Toolkit, NetworkX, and Matplotlib to efficiently sift through social web data as part of an experimentally-driven approach to discovering insights in social web data Apply advanced text-mining techniques such as TF-IDF, cosine similarity, collocation analysis, document summarization, and clique detection to human language data that you'll encounter all over the web Bootstrap interest graphs by discovering latent affinities between people, programming languages, and coding projects from GitHub data Visualize social web data with D3, a state-of-the-art HTML5 and JavaScript toolkit The ebook's source code is maintained in a GitHub repository maintained by the author and can be deployed as turn-key virtual machine with each chapter's source code presented in an interactive and easy to use IPython Notebook format. No complex third-party installations or advanced Python knowledge is required to get the most out of this ebook. All the code and most recent updates to the code can be found at github: https://github.com/ptwobrussell/Mining-the-Social-Web-2nd-Edition