Abstract
By nature, social networks exist and evolve; they arc dynamic. However the development in information technology increased the interest in social networks and they arc adapted to more applications and domains. To cope with the change, wc took the initiative and started three major projects, conference, journal and lecture notes scries that arc intended to meet the expectations of the involved research groups whose members have diverse backgrounds. This book is the first volume in our new scries entitled lecture notes in social networks. It includes papers that cover different topics ranging from fundamentals to applications of social networks.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Albert, R. and Barabási, A.L. Statistical mechanics of complex networks. Reviews of Modern Physics, 74(l):47–97, 2002.
Barabási, A.L. and Albert, R. Emergence of scaling in random networks. Science. 286(5439):509–512, 1999.
Baumes J., Goldberg M., Magdon-Ismail M. and Wallace W., “Discovering hidden groups in communication networks,” Proceedings of NSF/NIJ Symposium on Intelligence and Security Informatics. 2004.
Backstrom L., Huttenlocher D., Kleinberg J. and Lan X., “Group formation in large social networks: Membership, growth, and evolution,” Proceedings of ACM KDD, 2006.
Croft D. P., James R., Thomas P., Hathaway C, Mawdsley D., Laland K. and Krause J., “Social structure and co-operative interactions in a wild population of guppies (poecilia reticulata),” Behavioural Ecology and Sociobiology, Vol. 59, No.5, pp. 644–650, 2006.
Domingos, P. and Richardson, M. Mining the network value of customers. Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. San Francisco, CA: ACM Press, 2001.
Flake, G.W., Lawrence, S. et al. Efficient identification of web communities. Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Boston, MA: ACM Press, 2000.
Janssen, M.A. and Jager, W. Simulating market dynamics: Interactions between consumer psychology and social networks. Artificial Life, 9:343–356, 2003.
Jensen D. and Neville J., “Data mining in social networks,” Proceedings of the. Symposium on Dynamic Social Network Modeling and Analysis, 2002.
Kianmchr K. and Alhajj R., “Calling Communities Analysis and Identification Using Machine Learning Techniques,” Expert Systems with Applications, Vol. 36, No.3, pp. 6218–6226, 2009.
Klerks P., “The Network Paradigm Applied to Criminal Organisations: Theoretical nitpicking or a relevant doctrine for investigators? Recent developments in the Netherlands,” CONNECTIONS, Vol. 24, No.3, pp. 53–65, 2001.
Lawrence, S. and Giles, C.L. Accessibility of information on the web. Nature, 400:107–109, 1999.
Memon N. and Larsen H. L., “Structural Analysis and Mathematical Methods for Destabilizing Terrorist Networks,” Proceedings of the International Conference on Advanced Data Mining Applications, Springer-Verlag Lecture Notes in Artificial Intelligence (LNAI 4093), pp. 1037–1048, 2006.
Mcnczcr, F. Evolution of document networks. Proceedings of the National Academy of Science of the United States of America, 101:5261–5265, 2004.
Newman, M.E.J. The structure of scientific collaboration networks. Proceedings of the National Academy of Science of the United States of America, 98:404–409, 2001.
Pennock, D.M., Flake, G.W. et al. Winners don’t take all: Characterizing the competition for links on the web. Proceedings of the National Academy of Science of the United States of America, 99(8):5207–5211, 2002.
Powell, W.W., White, D.R. et al. Network dynamics and field evolution: The growth of interorganizational collaboration in the life sciences. American Journal of Sociology, 110(4):1132–1205, 2005.
Xu, J.J. and Chen, H. CrimcNct Explorer: A framework for criminal network knowledge discovery. ACM Transactions on Information Systems, 23(2):201–226, 2005.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag/Wien
About this chapter
Cite this chapter
Memon, N., Alhajj, R. (2010). Social Networks: A Powerful Model for Serving a Wide Range of Domains. In: Memon, N., Alhajj, R. (eds) From Sociology to Computing in Social Networks. Springer, Vienna. https://doi.org/10.1007/978-3-7091-0294-7_1
Download citation
DOI: https://doi.org/10.1007/978-3-7091-0294-7_1
Publisher Name: Springer, Vienna
Print ISBN: 978-3-7091-0293-0
Online ISBN: 978-3-7091-0294-7
eBook Packages: Computer ScienceComputer Science (R0)