Multi-state open opinion model based on positive and negative social influences

Abstract

Since the tremendous success of social networking websites, the related analytical research has been widely studied. Among these studies, social influence has been a significant and popular topic. We rely on the social influence model to predict and learn the influence diffusion process. However, traditional models only categorize nodes into two types of states, active and inactive. In addition, most previous models have only taken positive influences into account. Moreover, if inactive nodes are influenced successfully and turn into active nodes, these nodes cannot change their states forever. In this work, we not only break the above limitations but also propose a novel propagation method in our model. We proposes five states to represent the multiple states of influence. According to the new propagation method, the strength of the social influence may be reduced over time. Eventually, we utilize the measurement of precisions to compare with related models. The proposed multi-state model outperforms other two-state models in precisions of prediction. The experimental results show the superiority of multiple states.