Abstract
Internet chatrooms are common means of interaction and communications, and they carry valuable information about formal or ad-hoc formation of groups with diverse objectives. This work presents a fully automated surveillance system for data collection and analysis in Internet chatrooms. The system has two components: First, it has an eavesdropping tool which collects statistics on individual (chatter) and chatroom behavior. This data can be used to profile a chatroom and its chatters. Second, it has a computational discovery algorithm based on Singular Value Decomposition (SVD) to locate hidden communities and communication patterns within a chatroom. The eavesdropping tool is used for fine tuning the SVD-based discovery algorithm which can be deployed in real-time and requires no semantic information processing. The evaluation of the system on real data shows that (i) statistical properties of different chatrooms vary significantly, thus profiling is possible, (ii) SVD-based algorithm has up to 70-80% accuracy to discover groups of chatters.
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References
Kalt, C.: RFC 2810 Internet Relay Chat: Architecture (2000)
Kalt, C.: RFC 2811 Internet Relay Chat: Channel management (2000)
Kalt, C.: RFC 2812 Internet Relay Chat: Client protocol (2000)
Kalt, C.: RFC 2813 Internet Relay Chat: Server protocol (2000)
Johns, M.S.: RFC 1413 Identification Protocol (1993)
Gelhausen, A.: IRC statistics (1998), http://irc.netsplit.de (accessed 10 February 2004)
Mutton, P., Golbeck, J.: Visualization of semantic metadata and ontologies. In: Seventh International Conference on Information Visualization (IV 2003), pp. 300–305. IEEE, Los Alamitos (2003)
Mutton, P.: Piespy social network bot (2001), http://www.jibble.org/piespy/ (accessed 14 October 2003)
Viegas, F.B., Donath, J.S.: Chat circles. In: CHI 1999, ACM SIGCHI, pp. 9–16 (1999)
Krebs, V.: An introduction to social network analysis (2004), http://www.orgnet.com/sna.html (accessed 10 February 2004)
Magdon-Ismail, M., Goldberg, M., Siebecker, D., Wallace, W.: Locating hidden groups in communication networks using hidden markov models. In: Chen, H., Miranda, R., Zeng, D.D., Demchak, C.C., Schroeder, J., Madhusudan, T. (eds.) ISI 2003. LNCS, vol. 2665, pp. 126–137. Springer, Heidelberg (2003)
Goldberg, M., Horn, P., Magdon-Ismail, M., Riposo, J., Siebecker, D., Wallace, W., Yener, B.: Statistical modeling of social groups on communication networks. In: First conference of the North American Association for Computational Social and Organizational Science (CASOS 2003), Pittsburgh PA, CASOS (2003)
Golub, G.H., Loan, C.F.V.: Matrix Computations, 3rd edn. The Johns Hopkins University Press, Baltimore (1996)
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Çamtepe, A., Krishnamoorthy, M.S., Yener, B. (2004). A Tool for Internet Chatroom Surveillance. In: Chen, H., Moore, R., Zeng, D.D., Leavitt, J. (eds) Intelligence and Security Informatics. ISI 2004. Lecture Notes in Computer Science, vol 3073. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25952-7_19
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DOI: https://doi.org/10.1007/978-3-540-25952-7_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22125-8
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