An emotion-information spreading model in social media on multiplex networks

Abstract

The digital age has seen an exponential increase in the creation and dissemination of information, while the post-truth era has amplified the role of emotion in the spread of news. To prevent the outbreak of negative public sentiment due to uncontrolled emotional responses, it is critical to investigate the interplay between these two factors during the propagation. Therefore, we develop an emotion-information multiplex network based on the topic discussion function of social media. According to the influence of emotion on information transmission, emotion is divided into positive, negative and uninterested which are introduced into the standard SIR model. The microscopic Markov chain approach (MMCA) is used to analyze the outbreak threshold proving that emotion affects the threshold of information propagation. The extensive Monte Carlo (MC) simulations show that the average degree of information layer affects the emotional atmosphere. Secondly, the rapid dissemination of information will widen the emotional differences between people. Finally, positive or uninterested can easily become the dominant emotion of the group, and the group effect is more easily reflected in the user’s supportive attitude rather than the opposition attitude.