Modeling and Data Mining in Blogosphere (Synthesis Lectures on Data Mining and Knowledge Discovery)

✍ Scribed by Huan Liu, Nitin Agarwal

• Publisher: Morgan and Claypool Publishers
• Year: 2009
• Tongue: English
• Leaves: 113
• Series: Synthesis Lectures on Data Mining and Knowledge Discovery
• Category: Library

✦ Synopsis

This book offers a comprehensive overview of the various concepts and research issues about blogs or weblogs. It introduces techniques and approaches, tools and applications, and evaluation methodologies with examples and case studies. Blogs allow people to express their thoughts, voice their opinions, and share their experiences and ideas. Blogs also facilitate interactions among individuals creating a network with unique characteristics. Through the interactions individuals experience a sense of community. We elaborate on approaches that extract communities and cluster blogs based on information of the bloggers. Open standards and low barrier to publication in Blogosphere have transformed information consumers to producers, generating an overwhelming amount of ever-increasing knowledge about the members, their environment and symbiosis. We elaborate on approaches that sift through humongous blog data sources to identify influential and trustworthy bloggers leveraging content and network information. Spam blogs or "splogs" are an increasing concern in Blogosphere and are discussed in detail with the approaches leveraging supervised machine learning algorithms and interaction patterns. We elaborate on data collection procedures, provide resources for blog data repositories, mention various visualization and analysis tools in Blogosphere, and explain conventional and novel evaluation methodologies, to help perform research in the Blogosphere. The book is supported by additional material, including lecture slides as well as the complete set of figures used in the book, and the reader is encouraged to visit the book website for the latest information: http://tinyurl.com/mcp-agarwal Table of Contents: Modeling Blogosphere / Blog Clustering and Community Discovery / Influence and Trust / Spam Filtering in Blogosphere / Data Collection and Evaluation

✦ Table of Contents

Acknowledgments......Page 11
Modeling Blogosphere......Page 13
Modeling Essentials......Page 14
Preferential Attachment Blog Models......Page 20
Log-normal Distribution Models......Page 24
Blog Clustering and Community Discovery......Page 27
Graph Based Approach......Page 29
Content Based Approach......Page 33
Hybrid Approach......Page 36
Influence......Page 39
Graph Based Approach......Page 42
Content Based Approach......Page 45
Hybrid Approach......Page 46
Blog Leaders......Page 51
Trust......Page 52
Trust Computation......Page 53
Trust Propagation......Page 55
Spam Filtering in Blogosphere......Page 57
Graph Based Approach......Page 59
Content Based Approach......Page 61
Hybrid Approach......Page 63
API......Page 65
Web Crawler......Page 68
Available Datasets......Page 70
Data Preprocessing......Page 71
Blog Modeling......Page 72
Blog Clustering and Community Discovery......Page 73
Influence and Trust......Page 76
Spam......Page 80
Tools in Blogosphere......Page 83
API Examples......Page 91
Bibliography......Page 99
Biography......Page 107
Index......Page 109