How Collective Intelligence Restrains the Rumor Spreading in Emergencies? : -- Taking the COVID-19 Pandemic as an Example

Pinmo Wu; Xiaowen Qu; Zhuoxi Zhong

doi:10.54691/bcpssh.v16i.452

Authors

Pinmo Wu
Xiaowen Qu
Zhuoxi Zhong

DOI:

https://doi.org/10.54691/bcpssh.v16i.452

Keywords:

Public Health Emergency; Collective Intelligence; Rumor Spreading; Unconfirmed Information Dissemination (UID); Structural Equation Modeling (SEM).

Abstract

When communicating online under COVID-19 epidemic in 2020, all kinds of rumors are widely spread on the Internet. Coming with the spread of virus, the rumor spreading not only threaten the public health, but also facilitate panic and destroy the harmony of society. This study took the COVID-19 epidemic, a serious public health emergency, as an example. Firstly, we build up a Structural Equation Modeling (SEM) containing the influential factors of Collective Intelligence on unconfirmed information dissemination (UID) on social media, and then conduct an empirical test based on the survey data. The results show that the use of Collective Intelligence can restrain the spread of rumor in public health emergencies, among which critical thinking, collective refutation and proof, crowdsourcing and member heterogeneity are the main restraining factors. However, opinion leaders would facilitate the spread of rumor. This paper not only enriches the theory of Collective Intelligence and rumor management, but also has important practical significance for suppressing rumor spreading during the emergencies.

Downloads

Download data is not yet available.

References

Allport, G. W., & Postman, L. (1947). The psychology of rumor.

Chen, A., Wang, Z. J. & Chen, Sakura. (2020). The spread and governance of pseudoscientific online rumors in major public health events based on the SEIR model: Taking the new crown pneumonia epidemic as an example. Science and Technology Herald (04), 55-65.

Chen, H., De, P., Hu, Y. J., & Hwang, B. H. (2014). Wisdom of crowds: The value of stock opinions transmitted through social media. The Review of Financial Studies, 27(5), 1367-1403.

Chen, L. D. (2011). The circulation of rumors and opinions and the Web2.0 environment. Modern Communication (Journal of Communication University of China) (12), 110-115.

Dorigo, M., & Gambardella, L. M. (1997). Ant colonies for the travelling salesman problem. biosystems, 43(2), 73-81.

Ge, T., Xia, Z. J. & Yue Z. (2015). Analysis of factors affecting the dissemination of false information on social media by group wisdom. Intelligence Magazine (07), 152-156.

Halpern, D. F. (2013). Thought and knowledge: An introduction to critical thinking. Psychology Press.

Hao, Y. H. (2011). Cultural analysis of the wisdom of netizens. Contemporary Communication (05), 71-74.

Howe, J. (2006). The rise of crowdsourcing. Wired magazine, 14(6), 1-4.

Islam, M. S., Sarkar, T., Khan, S. H., Kamal, A. H. M., Hasan, S. M., Kabir, A., ... & Seale, H. (2020). COVID-19–related infodemic and its impact on public health: A global social media analysis. The American journal of tropical medicine and hygiene, 103(4), 1621.

Krause, J., Ruxton, G. D., & Krause, S. (2010). Swarm intelligence in animals and humans. Trends in ecology & evolution, 25(1), 28-34.

Li, H., & Sakamoto, Y. (2013). The influence of collective opinion on true-false judgment and information-sharing decision. Howe School Research Paper, (2013-8).

March, J. (2013). Handbook of organizations (RLE: Organizations). Routledge.

Mourad, A., Srour, A., Harmanani, H., Jenainati, C., & Arafeh, M. (2020). Critical impact of social networks infodemic on defeating coronavirus COVID-19 pandemic: Twitter-based study and research directions. IEEE Transactions on Network and Service Management, 17(4), 2145-2155.

Nance, W. (1995). Collective Intelligence in Computer-Based Collaboration, by John B. Smith (Book Review). Journal of the American Society for Information Science, 46(10), 793.

Nikolopoulos, K., Punia, S., Schäfers, A., Tsinopoulos, C., & Vasilakis, C. (2021). Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions. European journal of operational research, 290(1), 99-115.

Tanaka, Y., Sakamoto, Y., & Matsuka, T. (2013). Toward a social-technological system that inactivates false rumors through the critical thinking of crowds. In 2013 46th Hawaii International conference on system sciences (pp. 649-658). IEEE.

Tao, G. G. (2012). Internet Rumor Governance and Government Internet Public Opinion Guidance Capacity Building--Taking the "6.17" incident in Shishou, Hubei as an example. Yangtze River Forum (02), 61-65.

Wechsler, D. (1964). Die Messung der Intelligenz Erwachsener Huber. Bern Stuttgart Wien.

Zhang, L. B., Zhong, F. P., & Tu, H. (2012). Review of research on crowdsourcing issues. Science and Technology Progress and Countermeasures (06), 154-160.