Network probability matrix

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 <a href="/facts/Discrete_uniform_distribution/M52SQP5n">uniform random</a> 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 [year], 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.

<ul><li>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.</li>
<li>"Understanding Network Science," (Archived article) <a href="https://wayback-beta.archive.org/web/20080830045705/http://zangani.com/blog/2007-1030-networkingscience">https://wayback-beta.archive.org/web/20080830045705/http://zangani.com/blog/2007-1030-networkingscience</a></li>
<li>Linked: The New Science of Networks, A.-L. Barabási (Perseus Publishing, Cambridge (2002).</li>
<li>Network Science, The National Academies Press (2005)<a href="/facts/ISBN_(identifier)/15AdSPa9">ISBN</a> 0-309-10026-7</li></ul>

Network probability matrix open-in-new

Network probability matrix