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Kolophon | Rezensionen |
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JETZT ONLINE BESTELLEN
Mining the Social Web
Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites
First Edition Februar 2011
ISBN 978-1-4493-8834-8
350 Seiten,
EUR32.00
Kurzbeschreibung
Popular social networks such as Facebook and Twitter generate a tremendous amount of valuable data on topics and use patterns. Who’s talking to whom? What are they talking about? How often are they talking? This concise and practical book shows you how to answer these questions and more by harvesting and analyzing data using social web APIs, Python tools, GitHub, HTML5, and JavaScript.
Ausführliche Beschreibung
Want to tap the tremendous amount of valuable social data in Facebook, Twitter, LinkedIn, and Google+? This refreshed edition helps you discover who’s making connections with social media, what they’re talking about, and where they’re located. You’ll learn how to combine social web data, analysis techniques, and visualization to find what you’ve been looking for in the social haystack—as well as useful information you didn’t know existed.
Each standalone chapter introduces techniques for mining data in different areas of the social Web, including blogs and email. All you need to get started is a programming background and a willingness to learn basic Python tools.
- Get a straightforward synopsis of the social web landscape
- Use adaptable scripts on GitHub to harvest data from social network APIs such as Twitter, Facebook, LinkedIn, and Google+
- Learn how to employ easy-to-use Python tools to slice and dice the data you collect
- Explore social connections in microformats with the XHTML Friends Network
- Apply advanced mining techniques such as TF-IDF, cosine similarity, collocation analysis, document summarization, and clique detection
- Build interactive visualizations with web technologies based upon HTML5 and JavaScript toolkits
Weitere Informationen zu diesem Buch
Kolophon |
Rezensionen |
Ergänzende O'Reilly Titel:
![]() | Programming the Semantic Web |
![]() | Programming Collective Intelligence |
![]() | Learning Python |



