Information spreading in correlated microblog reposting network based on directed percolation theory

Abstract

Due to the properties of rapidity, explosive, timeliness and complicated behavior for user, the research on information spreading progress and influence factors for microblog becomes a hot area of network public opinion. In this paper, firstly we use the contracting mapping principle to discuss the convergence conditions of the iterative algorithm. The numerical solution of the percolation threshold and the size of the largest out-component are proposed. Then the influence of assortativity is analyzed based on the generation model with varying parameter. The feasibility of the proposed algorithm is verified by collecting microblog reposting data. Experimental results demonstrate that four correlation characteristics are shown to have assortativity and disassortativity, but the results of message spreading are closer to that of the assortative network which is related to in-in and in-out degree correlation. It can be verified that the four types of correlation characteristics of a large part of nodes show their consistency for assortativity, through deleting a few nodes as well as extracting link scale for four degree correlations.