A Dynamic Competition and Predation Model for Rumor and Rumor-Refutation

Abstract

The control of rumors spreading revolves around the interplay of the rumors and rumorrefuting information. Rumor-refuting information preys on the rumors, and competes with rumors for the same resource, netizens. There's both a predatory and competitive relationship between the rumors and rumor-refuting information. In this paper, we present a simple model to describe the interplay between rumors and rumor-refuting information based on biomathematics theory. By drawing from differential equations, A theoretical analysis reveals that this model exhibits three dynamic cases; extinction of rumors, extinction of rumor-refuting information and coexistence. And we study the stability of the equilibrium points of three cases, find that stable condition of equilibrium point, and show unstable case of model. Data from a micro-blog rumor about haze and the official micro-blog refuting this rumor were then crawled and the spreading process analyzed, and the haze rumors and rumor-refuting information evolution is estimated and forecasted by applying the mixture model. The integral method is deployed for the estimation of the model's parameters. Findings suggest that the rumors and the rumor-refuting information coexist in the case. and this case study is consistent with the theoretical analysis of coexistence. Based on this case, several scenarios were suggested to more deeply analyze the impact of the the effect of the authority's credibility and public cognition through the model. Finally, some policy suggestion for authorities that can contribute to rumor management in an emergency event.

Anti-Rumor Dissemination Model Based on Heat Influence and Evolution Game

“…At present, the research of some scholars mainly improves the classical information dissemination model, verifying that rumor and anti-rumor coexist and confirming that the network topology has a significant influence on the dissemination path and evolutionary process of public opinion information [6,7]. Therefore, many researchers have proposed improving the traditional information dissemination model from several aspects.…”

“…Jin et al constructed a rumor dissemination model based on content trust by considering three characteristics of rumors according to information content: the universality of the subject, the severity of influence and the ambiguity of events [11]. Zhang et al proposed a model based on biomathematics theory to study the interaction between rumors and rumor refutation and used the model to illustrate three dynamic situations about rumors: rumor extinction, rumor refutation extinction, rumor refutation and rumor coexistence [6]. Yin et al established a two-stage rumor dissemination model, in which rumor spreaders were divided into super infected and normal infected and vigilantes and rumor refuters were introduced to reflect the diversity of public opinion [12].…”

Configurational patterns for COVID-19 related social media rumor refutation effectiveness enhancement based on machine learning and fsQCA

“…On qualitative side, current research on false rumor refutation mainly focused on case-oriented study ( Chen, 2021 ; Zhang & Xu, 2021 ), the exploration from the perspective of psychology ( Manyika, 2013 ; Berinsky, 2017 ) and the perspective of news communication and management ( Paek & Hove, 2019 ; Dai, 2020 ). On quantitative side, researchers were more concerned about the identification of rumors and their influence factors of rumor spreading ( Liu, 2019 ; Lu, 2019 ), and the establishment of rumor spreading models ( Hosseini & Zandvakili, 2022 ; Guilherme, 2022 ).…”

A study on the competitive dissemination of disinformation and knowledge on social media

“…In the era of big data, social media has become the most important way for people to obtain information because of its convenience, timeliness and higher user value (Ma, 2020). However, as the social media continuously develops, the disinformation on social media has increased exponentially since people can obtain or send any information as they like at any time (Zhang and Xu, 2021). Disinformation will bring great harm to the healthy development of social media and social public safety, i.e.…”