Research on User Influence Model Integrating Personality Traits under Strong Connection
User influence has always been a major topic in the field of social networking. At present, most of the research focuses on three aspects: topological structure, social-behavioral dimension, and topic dimension and most of them ignore the difference between the audience. These models do not consider the impact of personality differences on user influences. To meet this need, this paper introduces the personality traits factor and proposes a user influence model which integrates personality traits (IPUIM) under a strong connection. The user influence measurement is constructed through the information dimension, structural dimension, and user behavioral dimension. The personality report of the user group is obtained by means of NEO-PI-R (The big five personality inventory, Chinese edition) and machine learning method, and it is integrated into the user influence model. The experiment proves that the model proposed in this paper has good accuracy and applicability in measuring user influence, and can effectively identify the key opinion leaders of different personality trait clusters.