Mining the social web/

By:

Russell, Matthew A

Material type: Text

TextPublication details: Mumbai: Shroff Publishers, O'Reilly, 2011Description: xx, 352pISBN:

9789350232941

Subject(s):

DDC classification:

006.312 RUS

Summary: 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 concise and practical book shows you how to answer these questions and more. You'll learn how to combine social web data, analysis techniques, and visualization to help you 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.

Item type:

Book

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Holdings
Item type	Current library	Call number	Status	Date due	Barcode
Book	IIM Kashipur	006.312 RUS (Browse shelf(Opens below))	Available		3016

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Previous	006.312 HSI Web dark: exploring and data mining the dark side of the web/	006.312 JAM Foundations of predictive analytics/	006.312 KUB Introduction to machine learning/	006.312 RUS Mining the social web/	006.32 DUN Data mining: introductory and advanced topics/	006.32 HAS Fundamentals of artificial neural networks/	006.33 APP Application of agents and intelligent information technologies/	Next

Includes bibliographical references and index.

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 concise and practical book shows you how to answer these questions and more. You'll learn how to combine social web data, analysis techniques, and visualization to help you 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.

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