Integrating the Theory of Planned Behavior and the Norm Activation Model to Explain Prosocial Rumour Refutation
Abstract
During emergency crises, the rapid spread of social media rumours can threaten public safety and social stability. Although users can play an important role in countering misinformation, user-led rumour refutation remains underexplored as a prosocial digital behaviour. This study develops an integrated psychosocial framework that combines the Theory of Planned Behaviour (TPB) and the Norm Activation Model (NAM) to explain the rational and moral drivers of the intention to refute rumours. Data from 565 active social media users were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM) in SmartPLS 4.0. The findings show that intention to refute rumours is significantly influenced by attitude, social norm, perceived behavioural control and, most strongly, personal norm. Awareness of consequences, ascribed responsibility and online respect also significantly influence attitudes towards rumour refutation. Theoretically, the study demonstrates the value of integrating behavioural and moral perspectives to explain proactive responses to misinformation. In practice, the findings suggest that platform managers and crisis communicators should strengthen users’ sense of responsibility, behavioural confidence, and respectful communication when designing misinformation interventions. Future research should examine the model across different populations, crisis contexts and digital platforms, and use longitudinal or experimental designs to assess whether these psychosocial factors translate into sustained rumour-refutation behaviour.
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Abbas, A. F., Jusoh, A., Mas’od, A., Alsharif, A. H., & Ali, J. (2022). Bibliometric analysis of information sharing in social media. Cogent Business & Management, 9(1), 2016556.
Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211.
Ali, I., Balta, M., & Papadopoulos, T. (2023). Social media platforms and social enterprise: Bibliometric analysis and systematic review. International Journal of Information Management, 69, 102510.
Al-Qaysi, N., Grani?, A., Al-Emran, M., Ramayah, T., Garces, E., & Daim, T. U. (2023). Social media adoption in education: A systematic review of disciplines, applications, and influential factors. Technology in Society, 102249.
Al-Zaman, M. S., Sife, S. A., Sultana, M., Akbar, M., Ahona, K. T. S., & Sarkar, N. (2020). Social media rumors in Bangladesh. Journal of Information Science Theory and Practice, 8(3), 77-90.
Azzimonti, M., & Fernandes, M. (2023). Social media networks, fake news, and polarization. European journal of political economy, 76, 102256.
De Groot, J. I., & Steg, L. (2009). Morality and prosocial behavior: The role of awareness, responsibility, and norms in the norm activation model. The Journal of Social Psychology, 149(4), 425-449.
De Groot, J. I., & Steg, L. (2010). Relationships between value orientations, self-determined motivational types and pro-environmental behavioral intentions. Journal of Environmental Psychology, 30(4), 368-378.
Ding, X., Zhang, X., Fan, R., Xu, Q., Hunt, K., & Zhuang, J. (2022). Rumor recognition behavior of social media users in emergencies. Journal of Management Science and Engineering, 7(1), 36-47.
Dougrez-Lewis, J., Kochkina, E., Arana-Catania, M., Liakata, M., & He, Y. (2022). PHEMEPlus: enriching social media rumor verification with external evidence. arXiv preprint arXiv:2207.13970.
Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: An organizational capabilities perspective. Journal of Management Information Systems, 18(1), 185–214.
Gorsuch, R. L. (1983). Factor Analysis (2nd Ed.). Hillsdale, NJ: Lawrence Erlbaum
Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., & Thiele, K. O. (2017). Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods. Journal of the Academy of Marketing Science, 45(5), 616–632.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24.
He, L., Gu, J., Li, D., & Lai, K. (2019, October). Content Characteristics and Transmission Strategies of Social Media Rumors in China: Big Data Analysis of WeChat Rumors. In 2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) (pp. 1-5). IEEE.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135.
Khraim, H. S. (2018). The Influence of Involvement and Awareness on UAE Women's Attitude Towards Fashion Clothing. International Journal of Marketing Studies, 10(2). https://doi.org/10.5539/ijms.v10n2p76
Kock, N. (2015). Common Method Bias in PLS-SEM. International Journal of e-Collaboration. 11, 1-10. 10.4018/ijec.2015100101.
Li, Z., Zhao, Y., Duan, T., & Dai, J. (2023). Configurational patterns for COVID-19-related social media rumor refutation effectiveness enhancement based on machine learning and fsQCA. Information Processing & Management, 60(3), 103303.
Masciandaro, D., Peia, O., & Romelli, D. (2024). Central bank communication and social media: From silence to Twitter. Journal of Economic Surveys, 38(2), 365-388.
Mirbabaie, M., Bunker, D., Stieglitz, S., Marx, J., & Ehnis, C. (2020). Social media in times of crisis: Learning from Hurricane Harvey for the coronavirus disease 2019 pandemic response. Journal of Information Technology, 35(3), 195-213.
Miró-Llinares, F., & Aguerri, J. C. (2023). Misinformation about fake news: A systematic critical review of empirical studies on the phenomenon and its status as a ‘threat’. European Journal of Criminology, 20(1), 356-374.
Nekmat, E., & Kong, D. (2019). Effects of online rumors on attribution of crisis responsibility and attitude toward organization during crisis uncertainty. Journal of Public Relations Research, 31(5-6), 133-151.
Pal, A., Chua, A. Y., & Goh, D. H. L. (2019). Debunking rumors on social media: The use of denials. Computers in Human Behavior, 96, 110-122.
Pavel, T. (2019). From Fake News to Virtual Reality - Fake News and Digital Manipulations at the Age of Modern Technology. Third Central European Cybersecurity Conference (CECC 2019).
Pundir, V., Devi, E. B., & Nath, V. (2021). Arresting fake news sharing on social media: a theory of planned behavior approach. Management Research Review, 44(8), 1108-1138.
Savari, M. & Bagher, K. (2023). Application of the extended theory of planned behavior in predicting the behavioral intentions of Iranian local communities toward forest conservation. Frontiers in Psychology. 14. 10.3389/fpsyg.2023.1121396.
Schwartz, S. H. (1977). Normative influences on altruism. In Advances in experimental social psychology (Vol. 10, pp. 221-279). Academic Press.
Shahzalal, M., & Adnan, H. M. (2022). Attitude, self-control, and prosocial norm to predict intention to use social media responsibly: From scale to model fit towards a modified theory of planned behavior. Sustainability, 14(16), 9822.
Shelke, S., & Attar, V. (2022). Rumor detection in social network based on user, content and lexical features. Multimedia Tools and Applications, 81(12). https://doi.org/10.1007/s11042-022-12761-y
Shen, Y. C., Lee, C. T., Pan, L. Y., & Lee, C. Y. (2021). Why people spread rumors on social media: developing and validating a multi-attribute model of online rumor dissemination. Online Information Review, 45(7), 1227-1246.
Tang, Z., Miller, A. S., Zhou, Z., & Warkentin, M. (2022). Understanding rumor combating behavior on social media. Journal of Computer Information Systems, 62(6), 1112-1124.
Tasnim, S., Hossain, M. M., & Mazumder, H. (2020). Impact of rumors and misinformation on COVID-19 in social media. Journal of preventive medicine and public health, 53(3), 171-174.
Torous, J., Bucci, S., Bell, I. H., Kessing, L. V., Faurholt?Jepsen, M., Whelan, P., ... & Firth, J. (2021). The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality. World Psychiatry, 20(3), 318-335.
Vrontis, D., Makrides, A., Christofi, M., & Thrassou, A. (2021). Social media influencer marketing: A systematic review, integrative framework and future research agenda. International Journal of Consumer Studies, 45(4), 617-644.
Xia, Z., Wu, Z., Wang, X., & Xie, Y. (2019). The quantitative simulation of social media rumors self-purification mechanism. Journal of Modern Information, 39(3), 103-110.
Yu, C. G., & Mustafa, H. (2023). Rumor response strategy and rumor behavioral intention: The mediating roles of anxiety on Chinese social media during COVID-19. SEARCH Journal of Media and Communication Research, 17-32.
Zhang, X., Gong, S., & Sinnott, R. O. (2021, December). Social media rumor detection through graph attention networks. In 2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE) (pp. 1-6). IEEE.
Zhao, L., Yin, J., & Song, Y. (2016). An exploration of rumor combating behavior on social media in the context of social crises. Computers in Human Behavior, 58, 25-36.
Zishan, Q., & Yijun, G. (2023). Detecting Social Media Rumors Based on Multimodal Heterogeneous Graph. Data Analysis and Knowledge Discovery, 7(11), 68-78.
Zubiaga, A., Liakata, M., Procter, R., Wong Sak Hoi, G., & Tolmie, P. (2016). Analyzing how people orient to and spread rumors in social media by looking at conversational threads. PloS one, 11(3), e0150989.
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