The convenience of the Internet has made it possible for activist groups to easily form alliances through their Websites to appeal to wider audience and increase their impact. In this study, we investigate the potential of using social network analysis (SNA) and Writeprints to discover the fusion of activitst ideas on the Internet, focusing on the Falun Gong movement. We find that network visualization is very useful to reveal how different types of Websites or ideas are associated and, in some cases, mixed together. Furthermore, the measures of centrality in SNA help to reveal which Websites most prominently link to other Websites. We find that Writeprints can be used to identify the ideas which an author gradually introduces and combines through a series of messages.
[Show abstract][Hide abstract] ABSTRACT: The social network paradigm provides a set of concepts and methods useful for studying the structure of a population through which infectious agents transmitted during close personal contact spread, and an opportunity to develop improved disease control programs. The research discussed was a first attempt to use a social network approach to better understand factors affecting the transmission of a variety of pathogens, including hepatitis B virus (HBV) and human immunodeficiency viruses (HIV), in a population of prostitutes, injecting drug users (IDU) and their personal associates in a moderate-sized city (Colorado Springs, CO). Some of the challenges of studying large social networks in epidemiological research are described, some initial results reported and a new view of interconnections in an at risk population provided. Overall, for the first time in epidemiologic research a large number of individuals (over 600) were found connected to each other, directly or indirectly, using a network design. The average distance (along observed social relationships) between persons infected with HIV and susceptible persons was about three steps (3.1) in the core network region. All susceptibles in the core were within seven steps of HIV infection.
Social Science & Medicine 02/1994; 38(1):79-88. DOI:10.1016/0277-9536(94)90302-6 · 2.89 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: As a result of growing misuse of online anonymity, researchers have begun to create visualization tools to facilitate greater user accountability in online communities. In this study we created an authorship visualization called Writeprints that can help identify individuals based on their writing style. The visualization creates unique writing style patterns that can be automatically identified in a manner similar to fingerprint biometric systems. Writeprints is a principal component analysis based technique that uses a dynamic feature-based sliding window algorithm, making it well suited at visualizing authorship across larger groups of messages. We evaluated the effectiveness of the visualization across messages from three English and Arabic forums in comparison with Sup- port Vector Machines (SVM) and found that Writeprints provided excellent classification performance, significantly outperforming SVM in many in- stances. Based on our results, we believe the visualization can assist law en- forcement in identifying cyber criminals and also help users authenticate fellow online members in order to deter cyber deception.
Intelligence and Security Informatics, IEEE International Conference on Intelligence and Security Informatics, ISI 2006, San Diego, CA, USA, May 23-24, 2006, Proceedings; 01/2006
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