The influence of cross-platform and spread sources on emotional information spreading in the 2E-SIR two-layer network

Shen, Han; Tu, Lilan; Guo, Yifei; Chen, Juan

doi:10.1016/j.chaos.2022.112801

Cited by 7 publications

(2 citation statements)

References 22 publications

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“…Usually, because of the idea of value exchange, self-presentation, or reputation enhancement [ 57 ], people are willing to share information that is positive, optimistic, or makes others feel good. Therefore, users affected by the positive emotion will exhibit stronger information-sharing behaviours.…”

Section: Research Model and Hypotheses Developmentmentioning

confidence: 99%

The Influence of Cognitive and Emotional Factors on Social Media Users’ Information-Sharing Behaviours during Crises: The Moderating Role of the Construal Level and the Mediating Role of the Emotional Response

2024

Behavioral Sciences

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Understanding the intricate dynamics of social media users’ information-sharing behaviours during crises is essential for effective public opinion management. While various scholarly efforts have attempted to uncover the factors influencing information sharing through different lenses, the underlying mechanisms remain elusive. Building upon the heuristic–systematic model (HSM) and construal level theory (CLT), this study explores the complex mechanisms that govern social media users’ information-sharing behaviours. The results indicate that both cognition and emotion play crucial roles in shaping users’ information-sharing behaviours, with systematic cues having the most significant impact on information-sharing behaviours. In terms of heuristic cues, positive emotions are more influential on information-sharing behaviours than primary cognition and negative emotions. Furthermore, spatial distance emerges as a key moderator, influencing individuals’ levels of engagement in information sharing. Emotion also acts as a mediator, connecting cognition to information sharing. This study provides insights into the sophisticated mechanisms of information sharing during crises, offering valuable implications for emergency management agencies to utilise social media for targeted public opinion guidance.

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Section: Research Model and Hypotheses Developmentmentioning

confidence: 99%

The Influence of Cognitive and Emotional Factors on Social Media Users’ Information-Sharing Behaviours during Crises: The Moderating Role of the Construal Level and the Mediating Role of the Emotional Response

2024

Behavioral Sciences

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“…However, it is not sufficient to characterize the delay caused by human cognitive processes [23] during information spread. Third, most models have not conducted further information spreading research similar to sensitivity analysis [24] for the model, which cannot objectively reflect the robustness of the model.…”

Section: Introductionmentioning

confidence: 99%

A Trend Prediction Method for Misinformation Spreading with Time Delay Effect

Zhang

Lin

Wang

et al. 2023

IEEJ Transactions Elec Engng

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Online social networks (OSNs) provide a platform for users to express opinions, discuss events and exchange ideas. However, the spread of misinformation in OSNs will interfere with users' judgment of useful information and may even cause significant economic losses to society. Exploring the spreading mechanism of misinformation in online social networks is the basis of eliminating the harm brought by misinformation to the network. Firstly, considering the influence of time delay on information spreading in real life, we propose a new misinformation spreading model to explore its spreading mechanism and describe its spreading process. Secondly, we provide the predictive method for studying the spread of misinformation in OSNs and theoretically demonstrate the stability of equilibrium points in the proposed information spreading model. Finally, we conduct simulation experiments based on a real dataset. The results show that compared to the benchmark model, our proposed model can reasonably explore the spreading mechanism and accurately predict the spreading trend of misinformation. Our proposed model and method can further establish a foundation for fast and effectively controlling the spread of misinformation and improving the controllability and efficiency of network communication and information spread. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

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