Evolutionary game analysis of online collective behaviour with the introduction of the degree of psychological identity
Bowen Li, Hua Li, Qiubai Sun, Xuebo Chen
Abstract
This article takes frequent online collective behaviour in the context of the outbreak of the 2019 Novel Coronavirus as its research background. Under the perspective of game theory, based on the Evolutionary Game Model and with the improvement of the model’s original parameter as well as the introduction of a new parameter, i.e. the degree of psychological identity netizens have on opinion leaders, this article constructs an evolutionary game model between opinion leaders and netizens, and applies numerical simulation to this model with MATLAB for further analysis. It is found that the decision of both opinion leaders and netizens is influenced by the following factors: the probability of a gloom-monger being punished by the government and the punishment intensity; the cost of investigation and evidence collection paid by opinion leaders and netizens; the degree to which netizens approve of opinion leaders’ statements with negative guidance; the extra profit earned by opinion leaders when statements with negative guidance are approved of and the total profit gained by netizens approving of statements released by opinion leaders. Conclusions can be applied as theories and decision-making references of the government when it comes to dealing with similar online collective behaviour in the future.