A physical pathway to understand individual's labeling behavior in signed social networks

In this paper we propose a reshuffling approach to empirical analyze individual's labeling behavior in signed social networks. In our approach, each individual is assumed to have the ability to re-label his/her neighbors randomly with the parameters ps and p+. Many reshuffled networks, which have the same topological structure and different signs' configuration, are built through applying our approach to the given three signed social networks. The entropy Sout and the giant component ρG for each reshuffled networks are calculated and analyzed. We find that there exist two kinds of individual's labeling behavior according to the suppressed effect of Sout and the exponent α in the relationship of ρG and q+. Additionally, the suppressed effect of Sout shows the non-randomness factor in individual's labeling behavior. These results offer new insights to understand human's behavior in online social networks.