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A statistical model of the impact of online rumors on the information quantity of online public opinion

Yuexin Lan, Zhixuan Lian, Runxi Zeng, Di Zhu, Yixue Xia, Mo Liu and Peng Zhang

Physica A: Statistical Mechanics and its Applications, 2020, vol. 541, issue C

Abstract: Current studies have considered the upper growth limit of the information quantity of online public opinion, although the effect of online rumors on the upper growth limit has not been considered. This study aims to identify the key parameters in a model of online rumors that affect the upper growth limit. First, the logistic population growth model is introduced to analyze the mechanism underlying the impact of online rumors on the information quantity of online public opinion. Second, the theory of differential equations is employed to build an influence rule between the two models. Third, we perform a numerical simulation to explore the development trend of the information quantity of online public opinion under the control of three parameters: rumor input rate, rumor conversion rate and rumor refutation rate. This paper defined the key factors for assessing how online public opinions are affected by online rumors, determined the influence strength of parameters under different online public opinion modes, better described the abnormal growth pattern of online public opinion, and provided a theoretical basis for online public opinion prediction and rumor control research.

Keywords: Rumor refutation; Online public opinion; Online rumors; Upper growth limit; Information quantity (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:541:y:2020:i:c:s0378437119320205

DOI: 10.1016/j.physa.2019.123623

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Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

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