A dynamic dissemination model for recurring online public opinion

Autor: Weiyao Tang, Jiuping Xu, Fengjuan Wang, Yi Zhang
Rok vydání: 2019
Předmět:
Zdroj: Nonlinear Dynamics. 99:1269-1293
ISSN: 1573-269X
0924-090X
DOI: 10.1007/s11071-019-05353-3
Popis: With an increasing number of people sharing feelings and opinions online, the online platforms have become one of the most important channels for public opinion dissemination. Moreover, recurring online public opinion has become a primary form of online public opinion and has begun to have major effects on prompting social change. Therefore, this paper establishes a novel dynamic dissemination model to systematically study the recurrence of online public opinion. Through an in-depth analysis, three major influencing factors are determined, a recurrence probability function is identified, and then a SIR-I-based dynamic dissemination model is successfully developed, for which the uniformly asymptotically stability is fully proved. A case study from “Child abuse in Ctrip kindergarten” is conducted to demonstrate the validity of the proposed model. The parameter analysis proved that controlling of the public opinion heat, control effectiveness, event topic relevance, and recurrence time point is an effective way to manage the recurrence dissemination, and that opinion leaders play an important role in dissemination. Meanwhile, comparative analysis shows that our model efficiently characterized the dissemination process of recurring online public opinion. As our paper expanded the research cycle of public opinion to its recurrence, it not only enriches online public opinion dissemination model development, but also provides a reference for quantitative analysis of recurring online public opinions dissemination.
Databáze: OpenAIRE
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