Knowledge Discovery from Online Communities

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Author(s): Luca Cagliero (Politecnico di Torino, Italy)and Alessandro Fiori (Politecnico di Torino, Italy)
Copyright: 2012
Pages: 23
Source title: Social Networking and Community Behavior Modeling: Qualitative and Quantitative Measures
Source Author(s)/Editor(s): Maytham Safar (Kuwait University, Kuwait)and Khaled Mahdi (Kuwait University, Kuwait)
DOI: 10.4018/978-1-61350-444-4.ch007

Keywords: Information Science Reference / Media & Communications / Social Computing / Social Networking

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Abstract

This chapter presents an overview of social network features such as user behavior, social models, and user-generated content to highlight the most notable research trends and application systems built over such appealing models and online media data. It first describes the most popular social networks by analyzing the growth trend, the user behaviors, the evolution of social groups and models, and the most relevant types of data continuously generated and updated by the users. Next, the most recent and valuable applications of data mining techniques to social network models and user-generated content are presented. Discussed works address both social model extractions tailored to semantic knowledge inference and automatic understanding of the user-generated content. Finally, prospects of data mining research on social networks are provided as well.

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