挖掘社交网络-第2版-(影印版)

preface  xii
part i.  a guided tour of the social web
prelude  !
　1. mining twitter: exploring trending topics, discovering what people are talking about,
　　and more  !
　　1.1. overview
　　1.2. why is twitter all the rage?
　　1.3. exploring twitter's api
　　1.3.1. fundamental twitter terminology
　　1.3.2. creating a twitter api connection
　　1.3.3. exploring trending topics
　　1.3.4. searching for tweets
　　1.4. analyzing the 140 characters
　　1.4.1. extracting tweet entities
　　1.4.2. analyzing tweets and tweet entities with frequency analysis
　　1.4.3. computing the lexical diversity of tweets
　　1.4.4. examining patterns in retweets
　　1.4.5. visualizing frequency data with histograms
　　1.5. closing remarks
　　1.6. recommended exercises
　　1.7. online resources
　2. mining facebook: analyzing fan pages, examining friendships, and more
　　2.1. overview
　　2.2. exploring facebook's social graph api
　　2.2.1. understanding the social graph api
　　2.2.2. understanding the open graph protocol
　　2.3. analyzing social graph connections
　　2.3.1. analyzing facebook pages
　　2.3.2. examining friendships
　　2.4. closing remarks
　　2.5. recommended exercises
　　2.6. online resources
　3. mining tinkedln: faceting job litles, clustering colleagues, and more
　　3.1. overview
　　3.2. exploring the linkedln api
　　3.2.1. making linkedln api requests
　　3.2.2. downloading linkedln connections as a csv file
　　3.3. crash course on clustering data
　　3.3.1. clustering enhances user experiences
　　3.3.2. normalizing data to enable analysis
　　3.3.3. measuring similarity
　　3.3.4. clustering algorithms
　　3.4. closing remarks
　　3.5. recommended exercises
　　3.6. online resources
　4. mining google+: computing document similarity, extracting collocations, and
　　4.1. overview
　　4.2. exploring the google+ api
　　4.2.1. making google+ api requests
　　4.3. a whiz-bang introduction to tf-idf
　　4.3.1. term frequency
　　4.3.2. inverse document frequency
　　4.3.3. tf-idf
　　4.4. querying human language data with tf-idf
　　4.4.1. introducing the natural language toolkit
　　4.4.2. applying tf-idf to human language
　　4.4.3. finding similar documents
　　4.4.4. analyzing bigrams in human language
　　4.4.5. reflections on analyzing human language data
　　4.5. closing remarks
　　4.6. recommended exercises
　　4.7. online resources
　5. mining web pages: using natural language processing to understand humad
　　language, summarize blog posts, and more……
　　5.1. overview

partll twitter cookbook
partll appendixes
a informarion about book's virtual machine experience
b oauth primer
c python and ipython notebook tips @ tricks
index