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首页 挖掘社交网络txt,chm,pdf,epub,mobi下载作者: Matthew A·Russell 出版社: 东南大学出版社 副标题: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites 原作名: Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites 出版年: 2011-5 页数: 332 定价: 78.00元 ISBN: 9787564126865 内容简介 · · · · · ·《挖掘社交网络(影印版)》,本书简洁而且具有操作性的书将为你展示如何回答这些甚至更多的问题,你将学到如何组合社交网络数据、分析技术,如何通过可视化帮助你找到你一直在社交世界中的内容。 作者简介 · · · · · ·马修·罗塞尔（Matthew A.Russell）,Digital Reasoning Systems公司的技术副总裁和Zaffra公司的负责人,是热爱数据挖掘、开源和Web应用技术的计算机科学家。他也是《Dojo: The Dofinitive Guide》（O'Reilly出版社）的作者。在LinkedIn上联系他或在Twitter上关注@ptwobrussell,可随时关注他的最新动态。 目录 · · · · · ·preface1. introduction: hacking on twitter data installing python development tools collecting and manipulating twitter data tinkering with twitter's apl frequency analysis and lexical diversity · · · · · ·() preface 1. introduction: hacking on twitter data installing python development tools collecting and manipulating twitter data tinkering with twitter's apl frequency analysis and lexical diversity visualizing tweet graphs synthesis: visualizing retweets with protovis closing remarks 2. microformats: semantic markup and common sense collide xfn and friends exploring social connections with xfn a breadth-first crawl of xfn data geocoordinates: a common thread for just about anything wikipedia articles + google maps = road trip? slicing and dicing recipes (for the health of it) collecting restaurant reviews summary 3. mailboxes: oldies but goodies .mbox: the quick and dirty on unix mailboxes mbox + couchdb = relaxed email analysis bulk loading documents into couchdb sensible sorting map/reduce-inspired frequency analysis sorting documents by value couchdb-lucene: full-text indexing and more threading together conversations look who's talking visualizing mail "events" with simile timeline analyzing your own mail data the graph your (gmail) inbox chrome extension closing remarks 4. twitter: friends, followers, and setwise operations restful and oauth-cladded apis no, you can't have my password a lean, mean data-collecting machine a very brief refactor interlude redis: a data structures server elementary set operations souping up the machine with basic friend/follower metrics calculating similarity by computing common friends and followers measuring influence constructing friendship graphs clique detection and analysis the infochimps "strong links" apl interactive 3d graph visualization summary 5. twitter: the tweet, the whole tweet, and nothing but the tweet pen: sword∷ tweet: machine gun (?!?) analyzing tweets (one entity at a time) tapping (tim's) tweets who does tim retweet most often? what's tim's influence? how many of tim's tweets contain hashtags? juxtaposing latent social networks (or #justinbieber versus #teaparty) what entities co-occur most often with #justinbieber and #teaparty tweets? on average, do #justinbieber or #teaparty tweets have more hashtags? which gets retweeted more often: #justinbieber or #teaparty? how much overlap exists between the entities of #teaparty and #justinbieber tweets? visualizing tons of tweets visualizing tweets with tricked-out tag clouds visualizing community structures in twitter search results closing remarks 6. linkedln: clustering your professional network for fun (and profit?) motivation for clustering clustering contacts by job title standardizing and counting job titles common similarity metrics for clustering a greedy approach to clustering hierarchical and k-means clustering fetching extended profile information geographically clustering your network mapping your professional network with google earth mapping your professional network with dorling cartograms closing remarks ?. 6oogle buzz: tf-idf, cosine similarity, and collocations buzz = twitter + blogs (???) data hacking with nltk text mining fundamentals a whiz-bang introduction to tf-idf querying buzz data with tf-idf finding similar documents the theory behind vector space models and cosine similarity clustering posts with cosine similarity visualizing similarity with graph visualizations buzzing on bigrams how the collocation sausage is made: contingency tables and scoring functions tapping into your gmail accessing gmail with oauth fetching and parsing email messages before you go off and try to build a search engine. closing remarks 8. blogs et al.: natural language processing (and beyond) nlp: a pareto-like introduction syntax and semantics a brief thought exercise a typical nlp pipeline with nltk sentence detection in blogs with nltk summarizing documents analysis of luhn's summarization algorithm entity-centric analysis: a deeper understanding of the data quality of analytics closing remarks 9. facebook: the all-in-one wonder tapping into your social network data from zero to access token in under 10 minutes facebook's query apis visualizing facebook data visualizing your entire social network visualizing mutual friendships within groups where have my friends all gone? (a data-driven game) visualizing wall data as a (rotating) tag cloud closing remarks 10. the semantic web: a cocktail discussion an evolutionary revolution? man cannot live on facts alone open-world versus closed-world assumptions inferencing about an open world with fuxi hope index · · · · · · () |
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作者： 软高林贵志
比较容易理解。
力荐
深深吸引了我
我很喜欢书,看的书越多,就会涉猎更广的书目