Mining the Social Web, 2E
Matthew A. Russell
- 出版商: O'Reilly
- 出版日期: 2013-10-20
- 定價: $1,575
- 售價: 5.0 折 $788
- 語言: 英文
- 頁數: 448
- 裝訂: Paperback
- ISBN: 1449367615
- ISBN-13: 9781449367619
-
相關分類:
Version Control、Data-mining
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商品描述
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.
商品描述(中文翻譯)
如何利用社交網絡的豐富數據，發現誰與誰建立了聯繫，他們在談論什麼，以及他們的位置在哪裡？通過這本擴展和全面修訂的新版，您將學習如何從社交網絡的各個角落獲取、分析和總結數據，包括Facebook、Twitter、LinkedIn、Google+、GitHub、電子郵件、網站和博客。
利用自然語言工具包（Natural Language Toolkit）、NetworkX和其他科學計算工具，從流行的社交網站中挖掘數據。
應用先進的文本挖掘技術，如聚類和TF-IDF，從人類語言數據中提取含義。
通過發現人、編程語言和編程項目之間的親和性，從GitHub中構建興趣圖。
使用D3.js建立交互式可視化工具，這是一個非常靈活的HTML5和JavaScript工具包。
利用O'Reilly流行的“問題/解決/討論”烹飪書格式，提供超過二十個Twitter配方。
這本獨特的數據科學書籍的示例代碼存放在公共的GitHub存儲庫中。它設計成通過一個即插即用的虛擬機器輕鬆訪問，並提供易於使用的IPython筆記本集合，以便進行互動學習。
