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2025-04-24
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。
評分本書介紹不同的社交網絡數據分析,由於內容比較寬導緻各個領域介紹的不是非常的深入。twitter一節有點過時瞭,互聯網發展太快瞭。本書代碼網址:https://github.com/ptwobrussell/Mining-the-Social-Web
評分作者的文風非常傲慢 源代碼各種不解釋 寫作思路跳躍性強難以捉摸 而且主要實現的功能偏數據收集 所謂的數據分析隻停留在淺層次上 好的地方是 接觸到瞭一些有趣的python庫:nltk做自然語言處理 networkx的網絡分析 graphvis做可視化 以及以couchdb為代錶的nosql 作為appetizer尚...
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yes, damn beaver -,-# 社交網站的DM需要用直推來隱藏看似復雜卻又簡單,做起來簡單卻確實不是隨便誰都能做好的工作。 UPLOAD YOUR SOUL TO THE ULTIMATE INTERNET!哈哈哈哈!
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
看瞭40%完全沒有內容啊
評分我覺得還好啊。。。。除瞭撐頁數的代碼
評分從對結構化、半結構化到無結構數據的分析和挖掘方法的介紹,雖然講的不是很深入、但是很有啓發。
評分我覺得還好啊。。。。除瞭撐頁數的代碼
評分有一種書,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...
Mining the Social Web 2025 pdf epub mobi 電子書 下載