Community Detection and Mining in Social Media

Nonfiction, Computers, Database Management, Data Processing, General Computing
Cover of the book Community Detection and Mining in Social Media by Lei Tang, Huan Liu, Morgan & Claypool Publishers
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Lei Tang, Huan Liu ISBN: 9781608453559
Publisher: Morgan & Claypool Publishers Publication: May 5, 2010
Imprint: Morgan & Claypool Publishers Language: English
Author: Lei Tang, Huan Liu
ISBN: 9781608453559
Publisher: Morgan & Claypool Publishers
Publication: May 5, 2010
Imprint: Morgan & Claypool Publishers
Language: English

The past decade has witnessed the emergence of participatory Web and social media, bringing people together in many creative ways. Millions of users are playing, tagging, working, and socializing online, demonstrating new forms of collaboration, communication, and intelligence that were hardly imaginable just a short time ago. Social media also helps reshape business models, sway opinions and emotions, and opens up numerous possibilities to study human interaction and collective behavior in an unparalleled scale. This lecture, from a data mining perspective, introduces characteristics of social media, reviews representative tasks of computing with social media, and illustrates associated challenges. It introduces basic concepts, presents state-of-the-art algorithms with easy-to-understand examples, and recommends effective evaluation methods. In particular, we discuss graph-based community detection techniques and many important extensions that handle dynamic, heterogeneous networks in social media. We also demonstrate how discovered patterns of communities can be used for social media mining. The concepts, algorithms, and methods presented in this lecture can help harness the power of social media and support building socially-intelligent systems. This book is an accessible introduction to the study of \emph{community detection and mining in social media}. It is an essential reading for students, researchers, and practitioners in disciplines and applications where social media is a key source of data that piques our curiosity to understand, manage, innovate, and excel. This book is supported by additional materials, including lecture slides, the complete set of figures, key references, some toy data sets used in the book, and the source code of representative algorithms. The readers are encouraged to visit the book website for the latest information. Table of Contents: Social Media and Social Computing / Nodes, Ties, and Influence / Community Detection and Evaluation / Communities in Heterogeneous Networks / Social Media Mining

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

The past decade has witnessed the emergence of participatory Web and social media, bringing people together in many creative ways. Millions of users are playing, tagging, working, and socializing online, demonstrating new forms of collaboration, communication, and intelligence that were hardly imaginable just a short time ago. Social media also helps reshape business models, sway opinions and emotions, and opens up numerous possibilities to study human interaction and collective behavior in an unparalleled scale. This lecture, from a data mining perspective, introduces characteristics of social media, reviews representative tasks of computing with social media, and illustrates associated challenges. It introduces basic concepts, presents state-of-the-art algorithms with easy-to-understand examples, and recommends effective evaluation methods. In particular, we discuss graph-based community detection techniques and many important extensions that handle dynamic, heterogeneous networks in social media. We also demonstrate how discovered patterns of communities can be used for social media mining. The concepts, algorithms, and methods presented in this lecture can help harness the power of social media and support building socially-intelligent systems. This book is an accessible introduction to the study of \emph{community detection and mining in social media}. It is an essential reading for students, researchers, and practitioners in disciplines and applications where social media is a key source of data that piques our curiosity to understand, manage, innovate, and excel. This book is supported by additional materials, including lecture slides, the complete set of figures, key references, some toy data sets used in the book, and the source code of representative algorithms. The readers are encouraged to visit the book website for the latest information. Table of Contents: Social Media and Social Computing / Nodes, Ties, and Influence / Community Detection and Evaluation / Communities in Heterogeneous Networks / Social Media Mining

More books from Morgan & Claypool Publishers

Cover of the book Social Monitoring for Public Health by Lei Tang, Huan Liu
Cover of the book Kinematic Labs with Mobile Devices by Lei Tang, Huan Liu
Cover of the book Web Corpus Construction by Lei Tang, Huan Liu
Cover of the book From Newton to Einstein by Lei Tang, Huan Liu
Cover of the book Quantum Metrology with Photoelectrons by Lei Tang, Huan Liu
Cover of the book Quantum Metrology with Photoelectrons by Lei Tang, Huan Liu
Cover of the book A Practical Guide to Testing Wireless Smartphone Applications by Lei Tang, Huan Liu
Cover of the book Introduction to Secure Outsourcing Computation by Lei Tang, Huan Liu
Cover of the book Social Media and Civic Engagement by Lei Tang, Huan Liu
Cover of the book Recognizing Textual Entailment by Lei Tang, Huan Liu
Cover of the book Introduction to Beam Dynamics in High-Energy Electron Storage Rings by Lei Tang, Huan Liu
Cover of the book SMath for Physics by Lei Tang, Huan Liu
Cover of the book The Manhattan Project by Lei Tang, Huan Liu
Cover of the book Optical Nanomanipulation by Lei Tang, Huan Liu
Cover of the book Airborne Maritime Surveillance Radar by Lei Tang, Huan Liu
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy