A Systems Dynamics Simulation Study of Network Public Opinion Evolution Mechanism

A Systems Dynamics Simulation Study of Network Public Opinion Evolution Mechanism

Ge Gao (Jilin University, Changchun, China), Tianyong Wang (Construction Environmental Protection Bureau of Hengqin New District, Zhuhai, China), Xianrong Zheng (Department of Information Technology and Decision Sciences, Old Dominion University, Norfolk, USA), Yong Chen (Texas A&M International University, Laredo, USA) and Xiaobo Xu (Department of Marketing and Information Systems, School of Business Administration, American University of Sharjah, Sharjah, UAE)
Copyright: © 2019 |Pages: 19
DOI: 10.4018/JGIM.2019100110

Abstract

The factors that affect formation and dissemination of public opinion have been studied for a long time. However, the findings are disparate and fragmented, given the characteristics of netizens and new media in the Big Data era. To this end, this article introduces eight mechanisms working on formation and dissemination of public opinion on network. Based on system dynamics, this article further proposes a comprehensive causal relationship model to explore the factors affecting the consequence of public opinion on network. Particularly, the role of government is taken into consideration in this model. A simulation with Vensim PLE is conducted. The results of the simulation indicate that group polarization among netizens, opinion leaders, the quantity of media audience, the frequency of media report, government attention, and warning mechanism for public opinion crisis affect the consequence of public opinion on network significantly. Implications of the findings are discussed.
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Introduction

Public opinion has been defined as a collection of views regarding an issue that affects many (Corbett, 1991). It is a process associated with multiple factors (Foote & Hart, 1953; Price & Roberts, 1987; Noelle-Neumann, 1993). According to Davison (1958), public opinion is “the result of psychological and social processes that lead to a situation in which the behavior of each member of a public in regard to an issue is conditioned by his expectation that other members of the public hold similar attitudes on the same issue” (p91). The narrow sense of public opinion is an expression of the general public’s attitudes about government, whereas the broad sense of public opinion is an expression of the general public’s living conditions, social environment, and attitudes on different issues (Katz & Lazarsfeld, 1955).

The study of the public opinion process often includes psychological components (attitudes and beliefs), social components (group discussion and norms), and political components (elite perspectives presented in the media) components (Hoffman, Glynn, Huge, Sietman, & Thomson, 2007). Two theories have been developed to explain how public opinion forms and influences people in the era of traditional media when a minority of members spread ideas to others in a society. One is the influentials theory, and the other is diffusion of innovations theory. According to these two theories, influentials play different roles in formation and dissemination of public opinion (Domingos & Richardson, 2001; Katz & Lazarsfeld, 1955; Rogers & Cartano, 1962; Watts & Dodds, 2007).

The development of new technologies, particularly the Internet, provides new platforms for formation and dissemination of public opinion (Cui & Jiang, 2018; Fan, 2017). Scholars have explored the characteristics of public opinion and how public opinion evolves on network. Particularly, diverse models have been proposed for studying public opinion. For example, Goldenberg, Libai, and Muller (2001) present a cascade model to explain the transmission process of public opinion on network. In addition, serval other models have been proposed in recent years, such as infection model (Su & Lan, 2013), network public opinion dredge model (Song, Zhu, & Huang, 2014), and system dynamics model (Di, Zeng, & Le, 2012). Recently, Zeng, Wang, and Chen (2014) compare several transmissions and spreading models for public opinion based on the macro and micro rules of public opinion.

Other than proposing models for studying public opinion, scholars have also explored the factors that affect public opinion. For instance, Chong and Druckman (2007b) point out that the transmission process in network affects the eruption and spreading of public opinion. Bennett and Iyengar (2008) investigate how audiences are affected by the development of network and the management of government when public opinion is transmitted in network. Ding (2015) explores how public opinion transmission evolved in network via simulation. Zhou, Wang, and Fang (2012) analyze the transmission mechanism of public opinion based on a case study. Chen and Chen (2016) adopts national cultural dimensions, the index of cultural distance, and the social influence theory to explore how culture impacts the opinion influence occurring in social media-based brand communities.

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