WorldCat Linked Data Explorer

Turtle N-Triple JSON-LD RDF/XML HTML Contact Us Home

http://worldcat.org/entity/work/id/815134384

Mining the social web

"How can you tap into the wealth of social web data to discover who's making connections with whom, what they're talking about, and where they're located? With this expanded and thoroughly revised edition, you'll learn how to acquire, analyze, and summarize data from all corners of the social web, including Facebook, Twitter, LinkedIn, Google+, GitHub, email, websites, and blogs. Employ the Natural Language Toolkit, NetworkX, and other scientific computing tools to mine popular social web sites. Apply advanced text-mining techniques, such as clustering and TF-IDF, to extract meaning from human language data. Bootstrap interest graphs from GitHub by discovering affinities among people, programming languages, and coding projects. Build interactive visualizations with D3.js, an extraordinarily flexible HTML5 and JavaScript toolkit. Take advantage of more than two-dozen Twitter recipes, presented in O'Reilly's popular "problem/solution/discussion" cookbook format The example code for this unique data science book is maintained in a public GitHub repository. It's designed to be easily accessible through a turnkey virtual machine that facilitates interactive learning with an easy-to-use collection of IPython Notebooks."--Amazon.com

Open All Close All

type

about

http://schema.org/about

alternateName

http://schema.org/alternateName

  • "Mining the social web: data mining Facebook, Twitter, Lindedin, Google+, Github, and more"@en
  • "Mining the social web : data mining facebook, twitter, linkedin, google+, github, and more"
  • "Mining the social web : analyzing Data from Facebook, twitter, Linkedln, and other social media sites"
  • "Mining the social web"@en
  • "Mining the social web"

author

contributor

creator

description

http://schema.org/description

  • "Na ovoju: "Facebook, Twitter, and LinkedIn generate a tremendous amount of valuable social data, but how can you find out who's making connections with social media, what they're talking about, or where they're located? This book shows you how to answer these questions and more. Each chapter introduces techniques for mining data in different areas of the social web, including blogs and email.""
  • ""How can you tap into the wealth of social web data to discover who's making connections with whom, what they're talking about, and where they're located? With this expanded and thoroughly revised edition, you'll learn how to acquire, analyze, and summarize data from all corners of the social web, including Facebook, Twitter, LinkedIn, Google+, GitHub, email, websites, and blogs. Employ the Natural Language Toolkit, NetworkX, and other scientific computing tools to mine popular social web sites. Apply advanced text-mining techniques, such as clustering and TF-IDF, to extract meaning from human language data. Bootstrap interest graphs from GitHub by discovering affinities among people, programming languages, and coding projects. Build interactive visualizations with D3.js, an extraordinarily flexible HTML5 and JavaScript toolkit. Take advantage of more than two-dozen Twitter recipes, presented in O'Reilly's popular "problem/solution/discussion" cookbook format The example code for this unique data science book is maintained in a public GitHub repository. It's designed to be easily accessible through a turnkey virtual machine that facilitates interactive learning with an easy-to-use collection of IPython Notebooks."--Amazon.com"@en
  • "" How can you tap into the wealth of social web data to discover who's making connections with whom, what they're talking about, and where they're located? With this expanded and thoroughly revised edition, you'll learn how to acquire, analyze, and summarize data from all corners of the social web, including Facebook, Twitter, LinkedIn, Google+, GitHub, email, websites, and blogs. Employ the Natural Language Toolkit, NetworkX, and other scientific computing tools to mine popular social web sites. Apply advanced text-mining techniques, such as clustering and TF-IDF, to extract meaning from human language data. Bootstrap interest graphs from GitHub by discovering affinities among people, programming languages, and coding projects. Build interactive visualizations with D3.js, an extraordinarily flexible HTML5 and JavaScript toolkit. Take advantage of more than two-dozen Twitter recipes, presented in O'Reilly's popular "problem/solution/discussion" cookbook format The example code for this unique data science book is maintained in a public GitHub repository. It's designed to be easily accessible through a turnkey virtual machine that facilitates interactive learning with an easy-to-use collection of IPython Notebooks."--Amazon.com"@en
  • "Facebook, Twitter, and LinkedIn generate a tremendous amount of valuable social data, but how can you find out who's making connections with social media, what they're talking about, or where they're located? This book shows you how to answer these questions and more. Each chapter introduces techniques for mining data in different areas of the social web, including blogs and email."@en
  • "Facebook, Twitter, and LinkedIn generate a tremendous amount of valuable social data, but how can you find out who's making connections with social media, what they're talking about, or where they're located? This book shows you how to answer these questions and more. Each chapter introduces techniques for mining data in different areas of the social web, including blogs and email."

genre

http://schema.org/genre

  • "Online-Publikation"
  • "Livre électronique (Descripteur de forme)"
  • "Electronic books"
  • "Electronic books"@en
  • "Ressource Internet (Descripteur de forme)"
  • "Libros electrónicos"
  • "Livres électroniques"

name

http://schema.org/name

  • "Mining the social web : [analyzing data from Facebook, Twitter, LinkedIn, and other social media sites : updated for Google+]"
  • "Mining the social web [analyzing data from Facebook, Twitter, LinkedIn, and other social media sites]"
  • "Mining the social web : [analyzing data from Facebook, Twitter, LinkedIn, and other social media sites]"
  • "Mining the social web data mining Facebook, Twitter, Linkedin, Google+, Github, and more"
  • "Mining the social web : data mining Facebook, Twitter, Linkedin, Google+, Github, and more"
  • "Mining the social web : [data mining from Facebook, Twitter, LinkedIn, Google+, GitHub and more]"
  • "Mining the Social Web"
  • "Mining the social web Includes index"
  • "Mining the social web : analyzing data from Facebook, Twitter, LinkedIn, and other social media sites"
  • "Mining the social web"
  • "Mining the social web"@en
  • "Mining the social web : anlyzing data from Facebook, Twitter, LinkedIn, and other social media sites"
  • "Mining the social web : [analyzing data from Facebook, Twitter, LinkedIn and other media sites]"
  • "Mining the social web : [data mining Facebook, Twitter, LinkedIn, Google+, Github, and more]"

workExample

http://schema.org/workExample