Agent-based opinion formation modeling in social network: A perspective of social psychology

Yin, Xicheng; Wang, Hongwei; Yin, Pei; Zhu, Hengmin

doi:10.1016/j.physa.2019.121786

Cited by 49 publications

(30 citation statements)

References 56 publications

(91 reference statements)

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“…Now, the balance point of the formation of network public opinion is found from the difference equation of the number of people among the three. Let the values of the difference equations (11) all be 0, and the equations (12) are expressed as follows:…”

Section: Direct Methodmentioning

confidence: 99%

Modeling, simulation, and case analysis of COVID‐19 over network public opinion formation with individual internal factors and external information characteristics

Chen

Peng

Yang

et al. 2021

Concurrency and Computation

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With the development of information technology, the Internet has become an important channel of public opinion for expressing public interests, emotion, and ideas. Public emergency usually spreads via network. Due to the temporal and spatial flexibility and the information amplification of network, the opinions from different regions and background are easy to be represented as network public opinion, and have important impact on social and economic life. Thus, studying the formation mechanism of network public opinion has important theoretical and practical significance. Taking the formation process of network public opinion under emergencies as the research object, this paper first identifies the key factors influencing the formation of network public opinion, namely the internal characteristics (include individual education level, individual stubbornness, individual initial opinion, and so on) and external information of individuals (include external information intensity). Second, information intensity is introduced to describe the influence of external information feature on the formation of network public opinion. Individual education level, individual stubbornness, and individual initial opinion are analyzed to describe the influence of individual internal factors on the formation, and then its model is constructed. Through the simulation experiments, this paper analyzes the influence of external information intensity, individual education level, individual stubbornness, individual initial opinion, and other factors on the formation of network public opinion. The simulation results show that: (1) the greater intensity of public emergency reporting causes the easier formation of network public opinion; (2) the higher individual education level leads to the shorter time for completing the final formation and stable state of online public opinions, and after the formation of online public opinions, the opinion of the event is mainly neutral; (3) the greater individual's stubbornness makes the shorter formation time of online public opinion. When online public opinion reaches a stable state, the neutral opinion group dominates and firmly controls the development trend of public opinion; (4) the difference of opinions among individuals is the most important factor affecting the formation of network public opinion. Finally, the rationality and validity of the proposed model are verified by a real case. Compared with previous studies on the formation mechanism of network public opinion, this paper divides the formation process of network public opinion into three stages: individual information perception, individual decision

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Section: Direct Methodmentioning

confidence: 99%

Modeling, simulation, and case analysis of COVID‐19 over network public opinion formation with individual internal factors and external information characteristics

Chen

Peng

Yang

et al. 2021

Concurrency and Computation

View full text Add to dashboard Cite

show abstract

“…Conversely, under safety-oriented social norms, workers' unsafe behaviors may be corrected. It can be explained by social psychology theory that human behavior, including mental activity, is the result of the individual interaction and is also influenced by a group environment [87]. However, most of the previous literature only focused on the mechanism of workers' individual cognitive processes.…”

Section: Sociocognitive Causes Of Unsafe Behavior Of Construction Wormentioning

confidence: 99%

Understanding the Sociocognitive Process of Construction Workers’ Unsafe Behaviors: An Agent-Based Modeling Approach

Yue

Yang

et al. 2020

IJERPH

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Previous literature has recognized that workers' unsafe behavior is the combined result of both isolated individual cognitive processes and their interaction with others. Based on the consideration of both individual cognitive factors and social organizational factors, this paper aims to develop an Agent-Based Modeling (ABM) approach to explore construction workers' sociocognitive processes under the interaction with managers, coworkers, and foremen. The developed model is applied to explore the causes of cognitive failure of construction workers and the influence of social groups and social organizational factors on the workers' unsafe behavior. The results indicate that (1) workers' unsafe behaviors are gradually reduced with the interaction with managers, foremen, and workers; (2) the foreman is most influential in reducing workers' unsafe behaviors, and their demonstration role can hardly be ignored; (3) the failure of sociocognitive process of construction workers is affected by many factors, and cognitive process errors could be corrected under social norms; and (4) among various social organizational factors, social identity has the most obvious effect on reducing workers' unsafe behaviors, and preventive measures are more effective than reactive measures in reducing workers' unsafe behaviors.

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“…First, numer-ous investigators focused on users' reactions to rumors. Yin [6] introduced psychology and sociology for analyzing the opinion interaction. Dang [7] investigated the psychological motivation of the rumor diffusion.…”

Section: Introductionmentioning

confidence: 99%

Modeling Repeated Rumor Spreading in Coupled Social Networks

et al. 2021

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Social networks are becoming increasingly collaborative and interdependent for achieving a broader market and profits. However, the coupled social networks which caused by the collaboration and interdependence bring more significant security risks. Rumors will spread more effectively and more rampant in coupled social networks than in separate social networks. Rumors spread in a single social network have attracted considerable attention. In coupled networks, whereas, the research remains to be explored. In coupled networks, in view of the fact that the public will face more rumors, this paper proposes a SIHR rumor spreading model with the "hesitation" psychological state for studying the dynamic course of rumors. The mean-field equation is given for describing and analyzing the diffusion course. The various propagation performances of SIHR model are explained by theoretical and experimental analysis. At last, targeted security scheme is discussed.

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Agent-based opinion formation modeling in social network: A perspective of social psychology

Cited by 49 publications

References 56 publications

Modeling, simulation, and case analysis of COVID‐19 over network public opinion formation with individual internal factors and external information characteristics

Modeling, simulation, and case analysis of COVID‐19 over network public opinion formation with individual internal factors and external information characteristics

Understanding the Sociocognitive Process of Construction Workers’ Unsafe Behaviors: An Agent-Based Modeling Approach

Modeling Repeated Rumor Spreading in Coupled Social Networks

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