Modeling and Data Mining in Blogosphere

Agarwal, Nitin|Liu, Huan

ISBN 10: 3031007700 / ISBN 13: 9783031007705

Verlag: Springer, Berlin|Springer International Publishing|Morgan & Claypool|Springer, 2009

Beschreibung

Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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.

Bestandsnummer des Verkäufers 608129156

Bibliografische Details

• Titel: Modeling and Data Mining in Blogosphere
• Verlag: Springer, Berlin|Springer International Publishing|Morgan & Claypool|Springer
• Veröffentlichungsdatum: 2009
• Sprache: Englisch
• ISBN-10: 3031007700
• ISBN-13: 9783031007705
• Bindung: Softcover
• Zustand: New
• Verkäuferkataloge:
  • Mathematik/Naturwissenschaften/Technik/Medizin

Über diesen Titel

Inhaltsangabe

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. Table of Contents: Modeling Blogosphere / Blog Clustering and Community Discovery / Influence and Trust / Spam Filtering in Blogosphere / Data Collection and Evaluation

Über die Autorin bzw. den Autor

Nitin Agarwal is a professor of Information Science at University of Arkansas at Little Rock. He received his Bachelor of Technology in Information Technology from Indian Institute of Information Technology, India, and Ph.D. in Computer Science from Arizona State University. He is one of the founding members of the Social Computing group in the Data Mining and Machine Learning Lab at ASU. His primary research interests include Social Computing, Knowledge Extraction in Social Media, Modeling Influence, Collective Wisdom, Familiar Strangers, and Model Evaluation. His work has resulted in publications in various prestigious forums including book chapters, encyclopedia entries, conferences and journals. His presentation at Web Search and Data Mining (WSDM 2008) conference on "Identifying the Influential Bloggers in a Community" recorded the highest number of hits (over 700) among all the talks at the conference. He co-presented a tutorial at the premiere data mining conference KDD 2008 on "Blogosphere: Research Issues, Applications, and Tools." He is a co-guest editor of a special issue on "Social Computing in Blogosphere" for IEEE Internet Computing magazine appearing (2010). Huan Liu is a professor of Computer Science and Engineering at Arizona State University. He received his Bachelor of Engineering from Shanghai Jiao Tong University and Ph.D. from University of Southern California, researched at Telecom Research Labs in Australia, and taught at National University of Singapore before he joined ASU. He has been recognized for excellence in teaching and research in CSE, ASU. His research interests are in data/web mining, machine learning, social computing, and artificial intelligence, investigating problems that arise in many real-world applications with high-dimensional data of disparate forms such as social media, modeling group interaction, text categorization, biomarker identification, and text/web mining. His research is sponsored by NSF, NASA, AFOSR, and ONR, among others. His well-cited publications include books, book chapters, encyclopedia entries as well as conference and journal papers. He serves on journal editorial boards and numerous conference program committees, and is a founding organizer of the International Workshop Series on Social Computing, Behavioral Modeling, and Prediction in Phoenix, AZ (SBP'08 and SBP'09). His professional memberships include AAAI, ACM, ASEE, and IEEE.