Blogs have become increasingly popular in recent years. Bloggers can express their opinions and emotions more freely and easily than before.Many communities have emerged in the blogosphere, including racist and hate groups that are trying to share their ideology, express their views, or recruit new group members. It is imperative to analyze these cyber communities in order to monitor for activities that are potentially harmful to society. Web mining and social network analysis techniques, which have been widely used to analyze the content and structure of Web sites of hate groups on the Internet, have not been applied to the study of hate groups in blogs. In this research, we present a framework, which consists of components of blog spider, information extraction, network analysis, and visualization, to address this problem (Chau & Xu, 2007). We applied this framework to identify and analyze a selected set of 28 anti-Blacks hate groups on Xanga, one of the most popular blog hosting sites. Our analysis results revealed some interesting demographical and topological characteristics in these groups, and identified at least two large communities on top of the smaller ones. We suggest that our framework can be generalized and applied to blog analysis in other domains.
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Chau, M., Xu, J. (2008). Using Web Mining and Social Network Analysis to Study The Emergence of Cyber Communities In Blogs. In: Chen, H., Reid, E., Sinai, J., Silke, A., Ganor, B. (eds) Terrorism Informatics. Integrated Series In Information Systems, vol 18. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-71613-8_22
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