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The network probability matrix describes the probability structure of a network based on the historical presence or absence of edges in a network. For example, individuals in a social network are not connected to other individuals with uniform random probability. The probability structure is much more complex. Intuitively, there are some people whom a person will communicate with or be connected more closely than others. For this reason, real-world networks tend to have clusters or cliques of nodes that are more closely related than others (Albert and Barabasi, 2002, Carley , Newmann 2003). This can be simulated by varying the probabilities that certain nodes will communicate. The network probability matrix was originally proposed by Ian McCulloh.
References
- McCulloh, I., Lospinoso, J. & Carley, K.M. (2007). Probability Mechanics in Communications Networks. In Proceedings of the 12th International Conference on Applied Mathematics of the World Science Engineering Academy and Society, Cairo, Egypt. 30–31 December 2007.
- "Understanding Network Science," (Archived article) https://wayback-beta.archive.org/web/20080830045705/http://zangani.com/blog/2007-1030-networkingscience
- Linked: The New Science of Networks, A.-L. Barabási (Perseus Publishing, Cambridge (2002).
- Network Science, The National Academies Press (2005)ISBN 0-309-10026-7
External links
- Center for Computational Analysis of Social and Organizational Systems (CASOS) at Carnegie Mellon University
- U.S. Military Academy Network Science Center
- The Center for Interdisciplinary Research on Complex Systems at Northeastern University
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