Modelling the dynamic emotional information propagation and guiding the public sentiment in the Chinese Sina-microblog

Social networks are flooded with different pieces of emotional information, the propagation of which helps to shape the development of public sentiment. To help designing effective communication strategies during the entire development of an event, we propose an emotion-based susceptible-forwarding-immune (E-SFI) propagation dynamic model, that takes into account of the categories of emotions into positive, neutral and negative and the emotional choices of user communities, to investigate the information propagation process that leads to public sentiment. Our model is based on the forwarding quantity and takes into account the differential influence of a delivered emotional information on the emotion change of users depending on their respective emotion status. Our Model-based analytic and numerical analyses show that three types of forwarding probabilities involved in our E-SFI model are in accordance with the actual accident situation, and our sensitivity analyses describe important factors that affect the emotional choices of user communities in support for decision strategies to guide the public sentiment. To quantify the significance of these factors, we introduce multiple summative indices including the information with emotions propagation reproduction number, and emotion entropy.