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- 426pages
- 15 heures de lecture
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Want to tap the tremendous amount of valuable social data in Facebook, Twitter, LinkedIn, GitHub, Instagram, and Google+? This new 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. Get a straightforward synopsis of the social web landscape Use adaptable scripts on GitHub to harvest data from social network APIs. 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, clique detection, and image recognition Build interactive visualizations with web technologies based upon HTML5 and JavaScript toolkits
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Mining the Social Web, Matthew A. Russell, Mikhail Klassen
- Langue
- Année de publication
- 2019
- product-detail.submit-box.info.binding
- (souple)
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- Titre
- Mining the Social Web
- Sous-titre
- Data Mining Facebook, Twitter, LinkedIn, Instagram, GitHub, and More
- Langue
- Anglais
- Auteurs
- Matthew A. Russell, Mikhail Klassen
- Éditeur
- O'Reilly Media
- Publié
- 2019
- Format
- souple
- Pages
- 426
- ISBN10
- 1491985046
- ISBN13
- 9781491985045
- Séries
- Mots clés
- Nonfiction, Informatique & Internet, Langues, Technologie, Internet, Aspects sociaux, Analyse de données, Traitement des données, Réseaux informatiques
- Description
- Want to tap the tremendous amount of valuable social data in Facebook, Twitter, LinkedIn, GitHub, Instagram, and Google+? This new 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. Get a straightforward synopsis of the social web landscape Use adaptable scripts on GitHub to harvest data from social network APIs. 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, clique detection, and image recognition Build interactive visualizations with web technologies based upon HTML5 and JavaScript toolkits