Modeling Network Public Opinion Propagation with the Consideration of Individual Emotions

Abstract

The occurrence of popular social events causes fluctuations and changes of public emotions, while the rapid development of online social platforms and networks has made individual interactions more intense and further escalated public emotions into public opinion. However, there is a lack of consideration of individual emotions in the current research on online public opinion. Based on this, this paper firstly expounds the quantitative representation of attitude and emotion, analyzes the formation and propagation process of online public opinion by combining individual’s expression willingness, individual’s expression ability, attitude perception value, attitude change probability and other factors, and constructs a network public opinion propagation model that takes individual emotion into consideration. Finally, the main factors affecting the formation and propagation of network public opinion are discussed through simulation experiments. The results demonstrate that: (1) fear is conducive to the formation of online public opinion, but the speed is relatively slow; sadness is not conducive to the formation, but once enough people participate in the exchange of views, the formation of online public opinion will be faster; (2) the influence of online public opinion on individual emotions expands with the increase of the number of individual interactions; (3) different network structures impact differently on the propagation of public opinion. Among them, BA (BA network is a scale-free network model proposed by Barabasi and Albert in order to explain the generation mechanism of power law, BA model has two characteristics: growth and priority connection mechanism) and ER (ER network is a network with random connectivity proposed by Erdös-Renyi) random networks can promote the propagation of online public opinion, which is prone to “one-sided” online public opinion. WS small-world networks (proposed by Watts and Strogatz. It is a kind of network with short average path length and high clustering coefficient) and fully-connected networks have an inhibitory effect on the spread of online public opinion, easily maintaining the multi-dimensional nature of online public opinion.

Investigating the Public Sentiment in Major Public Emergencies Through the Complex Networks Method: A Case Study of COVID-19 Epidemic

“…The same exchange of news, information, or media has a peak in different emotions, which results in a mixture of positive and negative emotions. This can be explained by the fact that confiding needs and dissatisfaction on the public platform is a process through which people relieve pressure; however, seeing other people's negative demands can create empathy and amplify negative emotions ( 43 ). At the same time, the public is more inclined to forward emotional microblogs, especially those with negative emotions, than to forward microblogs with neutral emotions ( 44 ).…”

Modeling, simulation, and case analysis of COVID‐19 over network public opinion formation with individual internal factors and external information characteristics

“…There are still some deficiencies in this paper: The undiscussed issues in this paper, such as psychological change of Internet users, 32,33 the leading role of the media, 34,35 and the mood of opinion leaders, 36,37 will all affect the formation of network public opinion, but they are difficult to be quantified. Therefore, future work needs to be further integrated into the model, and studies the effect of three factors on the network public opinion formation. In the simulation analysis, the influence of relevant parameters on the formation of network public opinion is highly discussed from the macro‐level 38,39 .…”

“…1. The undiscussed issues in this paper, such as psychological change of Internet users, 32,33 the leading role of the media, 34,35 and the mood of opinion leaders, 36,37 will all affect the formation of network public opinion, but they are difficult to be quantified. Therefore, future work needs to be further integrated into the model, and studies the effect of three factors on the network public opinion formation.…”

Research on the Emotional Evolution Mechanism of Network Public Opinion Based on an Information Ecosystem

“…is the belief factor, r ∈ [0, 1] is suspicion factor, and k ∈ [0, 1] is the emotion transfer factor; n ∈ [1,3] is the number of times that the ignorant person comes in contact with the information of different infected persons. α n represents the probability that the unknown person is exposed to n times of positive or negative information and turns into the immune.…”

“…Due to the virtual and anonymous nature of the Internet [1], the Internet has become an important gathering place to express public interests, emotions, and thoughts [2]. When public expression gradually accumulated and externalized into attitudes, netizens' opinions collided with each other in communication and discussion, thus promoting the formation of online public opinions [3]. In essence, the development of online public opinion is the result of competition between positive and negative emotions [4].…”