Thus the proposed PageRank Opinion Formation (PROF) model takes into account the situation in which an opinion of an in?uential friend from high ranks of the society counts more than an opinion of a friend from lower society level. We argue that the PageRank probability is the most natural form of ranking of society members. Indeed, the e?ciency of PageRank rating is demonstrated for various types of scale-free networks including the World Wide Web (WWW), Physical Review citation network, scienti?c journal rating, ranking of tennis players, Wikipedia articles, the world trade network and others. Due to the above argument we consider that the PROF model captures the reality of social networks and below we present the analysis of its interesting properties.
I've posted four distinct articles describing various methods for modeling the #attentioneconomy today, in case anyone happened to notice. Hopefully the scientists involved are also working on popularized texts to help the public understand what they are doing. I'm trying to describe it as best I can, but I'm worried that the science is outpacing my attempts to clarify. I think that's a good kind of problem. I'm really not sure.
Kenneth Read originally shared this post:
PageRank. Imagine simulating or even predicting opinion formation on large social networks, and the preservation of opinions in small circles. Are the tools of theoretical physics relevant and up to the challenge?… Boltzmann meets Twitter tonight.
Abstract: We propose the PageRank model of opinion formation and investigate its rich properties on real directed networks of Universities of Cambridge and Oxford, LiveJournal and Twitter. In this mod…