Abstract
In social networks, opinions diffusion often leads to relationships evolution. Then changes of relationships result in the change of balance degree of social system. We simulate the opinion diffusion on Barabasi & Albert (BA) network and Watts & Strogatz (WS) network to study the effects of the two types of networks, dynamical parameters and structural parameters on the balance degree of system. We employ the spectral analysis to quantify the balance degree of system before and after opinion propagation. The result reveals that it is very similar effect of BA networks and WS networks on it. However, it is opposite effects between dynamical parameters and structural parameters. The balance degree of system is proportional to the two dynamical factors (P,Q) at initial state and always inversely proportional to the two structural factors (,Pne) at initial and convergence state.
Highlights
IntroductionOpinion propagation always impacts interpersonal relationships in some degree
In a community, opinion propagation always impacts interpersonal relationships in some degree
We simulate the opinion diffusion on Barabási & Albert (BA) network and Watts & Strogatz (WS) network to study the effects of the two types of networks, dynamical parameters and structural parameters on the balance degree of system
Summary
Opinion propagation always impacts interpersonal relationships in some degree It has been a challenge for researchers to figure out the rule and the characteristic about the impact by opinion propagation in different social structure. We employ the Heider theory [16] of structural balance (i.e., social balance) to evaluate social relationship. Heider [16,17] postulates the triad with exactly odd negative edge to be unbalanced and the unbalance triad trends to be balance. Cartwright et al [19] extended and generalized the balance theory from 3-circle to n-circle (n ≥ 3) They postulates that n-circle with odd negative edge is unbalanced. We use the spectral analysis method to calculate the smallest eigenvalue to measure the balance degree of the whole network. The smaller the smallest eigenvalue is, the more stable the whole social system is and the more harmonious the social relationships are, vice versa
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