Matthew Russell has completed nearly 50 publications on technology, including work that has appeared at scientific conferences and in Linux Journal and Make magazine. He is also the author of Dojo: The Definitive Guide (O’Reilly). Matthew is Vice President of Engineering at Digital Reasoning Systems and is Founder & Principal at Zaffra, a firm focused on agile web development.
Popular social networks such as Facebook, Twitter, and LinkedIn generate a tremendous amount of valuable social data. Who's talking to whom? What are they talking about? How often are they talking? Where are they located? This concise and practical book shows you how to answer these types of questions and more. Each chapter presents a soup-to-nuts approach that combines popular social web data, analysis techniques, and visualization to help you find the needles in the social haystack you've been looking for -- and some you didn't know were there.
With Mining the Social Web, intermediate-to-advanced Python programmers will learn how to collect and analyze social data in way that lends itself to hacking as well as more industrial-strength analysis. The book is highly readable from cover to cover and tells a coherent story, but you can go straight to chapters of interest if you want to focus on a specific topic.
Get a concise and straightforward synopsis of the social web landscape so you know which 20% of the space to spend 80% of your time on
Use easily adaptable scripts hosted on GitHub to harvest data from popular social network APIs including Twitter, Facebook, and LinkedIn
Learn how to slice and dice social web data with easy-to-use Python tools, and apply more advanced mining techniques such as TF-IDF, cosine similarity, collocation analysis, document summarization, and clique detection
Build interactive visualizations with easily adaptable web technologies built upon HTML5 and JavaScript toolkits
This book is still in progress, but you can get going on this technology through our Rough Cuts edition, which lets you read the manuscript as it's being written, either online or via PDF.
via http://oreilly.com/catalog/9781449394844/
Amazon: http://www.amazon.com/Mining-Social-Web-Finding-Haystack/dp/1449388345/
作者的文风非常傲慢 源代码各种不解释 写作思路跳跃性强难以捉摸 而且主要实现的功能偏数据收集 所谓的数据分析只停留在浅层次上 好的地方是 接触到了一些有趣的python库:nltk做自然语言处理 networkx的网络分析 graphvis做可视化 以及以couchdb为代表的nosql 作为appetizer尚...
评分虽然使用的语言是python,而且分析的网站都是国内被禁的网站,但是读完这本书后,感到很受启发,其实如果你懂了这本书中的内容,分析其他社交网站也会得心应手,比如说像国内的sina微博,人家提供的API也很有价值啊,你读完这本书,收获会很大。
评分Popular social networks such as Facebook, Twitter, and LinkedIn generate a tremendous amount of valuable social data. Who's talking to whom? What are they talking about? How often are they talking? Where are they located? This concise and practical book sho...
评分如果你希望从这本书里边学到任何软件使用方法以外的东西,我觉得你会失望的。 因为从第七章开始才讲算法,还将得各种悲剧。直接看wikipedia都能理解得更快。 之前的章节都是各个社交网络API的介绍和工具使用介绍,还算行吧。 里边提到的工具目录里边基本都有,直接上官方站...
评分虽然使用的语言是python,而且分析的网站都是国内被禁的网站,但是读完这本书后,感到很受启发,其实如果你懂了这本书中的内容,分析其他社交网站也会得心应手,比如说像国内的sina微博,人家提供的API也很有价值啊,你读完这本书,收获会很大。
一般吧
评分Enhanced book of 《社会网络分析-方法与实践》
评分看了40%完全没有内容啊
评分:无
评分目前只看了一半。统计方面的知识是没怎么介绍,但对web环境、工具的介绍让我受益很大。Microformats, CouchDB, Redis, Graphviz..
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