2012/11/30 by Shankar Bhamidi, J. Michael Steele, Tauhid Zaman
Mathematics · #math.PR
paper · pdf · doi:10.1214/14-aap1053
published as Annals of Applied Probability 2015, Vol. 25, No. 5, 2462-2502 · Published at http://dx.doi.org/10.1214/14-AAP1053 in the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)
arxiv created 2015/09/09 · arxiv updated 2015/09/10
Condensation phenomenon is often observed in social networks such as Twitter where one "superstar" vertex gains a positive fraction of the edges, while the remaining empirical degree distribution still exhibits a power law tail. We formulate a mathematically tractable model for this phenomenon that provides a better fit to empirical data than the standard preferential attachment model across an array of networks observed in Twitter. Using embeddings in an equivalent continuous time version of the process, and adapting techniques from the stable age-distribution theory of branching processes, we prove limit results for the proportion of edges that condense around the superstar, the degree distribution of the remaining vertices, maximal nonsuperstar degree asymptotics and height of these random trees in the large network limit.