摘要
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 p(s) 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 S-out and the giant component rho(G) 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 S-out and the exponent alpha in the relationship of rho(G) and q(+). Additionally, the suppressed effect of S-out shows the non-randomness factor in individual's labeling behavior. These results offer new insights to understand human's behavior in online social networks.
- 出版日期2018-11-9
- 单位中国地质大学(武汉)