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/
發表於2025-03-29
Mining the Social Web 2025 pdf epub mobi 電子書 下載
原本是想學些數據分析的算法和思想,但是拿到這本書之後挺失望。看到第四章,全在講如何使用twitter等社交網站的api。 隻能當拓展知識麵看看,瞭解下書裏麵講到的開源工具。 另外,書的價格還不算便宜。
評分評價給的是原書的。 本來是一本還不錯的書,看著那些翻譯的語句,哎,真操蛋,這是我直接扔垃圾桶的第一本書,翻譯的真不行。 再說書的內容,大概過瞭一遍,內容挺豐富的,包括瞭郵件、twitter、facebook、linkedin等各個方麵的挖掘想法、工具,還是不錯的。對於數據分析的關鍵...
評分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...
評分雖然使用的語言是python,而且分析的網站都是國內被禁的網站,但是讀完這本書後,感到很受啓發,其實如果你懂瞭這本書中的內容,分析其他社交網站也會得心應手,比如說像國內的sina微博,人傢提供的API也很有價值啊,你讀完這本書,收獲會很大。
評分原本是想學些數據分析的算法和思想,但是拿到這本書之後挺失望。看到第四章,全在講如何使用twitter等社交網站的api。 隻能當拓展知識麵看看,瞭解下書裏麵講到的開源工具。 另外,書的價格還不算便宜。
圖書標籤: 數據挖掘 社會化網絡 數據分析 sns Social Web O'Reilly 互聯網
有一種書,頂著時下流行的名詞,打著實踐的口號,整段整段的貼代碼,介紹各種工具,這類書,每頁看一段,每段看一句就差不多瞭...比如mining the social web...
評分我覺得還好啊。。。。除瞭撐頁數的代碼
評分不容易,終於讀完瞭。
評分很實用,寓教於樂
評分python庫一日遊哈哈哈~
Mining the Social Web 2025 pdf epub mobi 電子書 下載