Exploring the Determinants of Sharing Refutation Information on Social Media: Insights from Media Affordance Theory
DOI:
https://doi.org/10.71222/bb5q3v21Keywords:
social media platforms, media affordance theory, debunking information, Stimulus-Organism-Response modelAbstract
With the rapid evolution of technology, social media platforms have emerged as vital channels for disseminating debunking information. This study examines the mechanisms through which media affordances affect users' willingness to share such content, taking a technological perspective. The goal is to explore how the affordances offered by media platforms enhance the effectiveness of debunking efforts, facilitating the more efficient use of these technological tools. Drawing upon the theoretical foundations of media affordance theory and the Stimulus-Organism-Response (S-O-R) model, this research develops a framework to assess social media users' readiness to share debunking information. A survey was conducted, gathering 308 valid responses, which were analyzed through structural equation modeling. The findings indicate that five key dimensions of social media platforms—media flexibility, user agency, emotional expressiveness, social connectivity, and 24/7 push notifications—positively and significantly influence users' perceptions of debunking content and their willingness to share it.
References
1. Zhao, J. Yin, and Y. Song, "An exploration of rumor combating behavior on social media in the context of social crises," Comput. Hum. Behav., vol. 58, pp. 25–36, 2016, doi: 10.1016/j.chb.2015.11.054.
2. X. Wang, M. Chen, and W. Jiang, "Why is one social media platform not enough? A typology of platform-swinging behavior and associated affordance preferences," Soc. Media + Soc., vol. 2, 2024, doi: 10.1177/20563051241254373.
3. J. J. Gibson, The Ecological Approach to Visual Perception: Classic Edition, Psychology Press, 2014, doi: 10.4324/9781315740218.
4. Y. Jianghua and Z. Mengzhu, "Beyond structural inequality: A socio-technical approach to the digital divide in the platform environment," Humanit. Soc. Sci. Commun., vol. 1, 2023, doi: 10.1057/S41599-023-02326-1.
5. K. Zhao, Y. Hu, Y. Hong, and C. Westland, "Understanding characteristics of popular streamers on live streaming platforms: Evidence from Twitch.tv," J. Assoc. Inf. Syst., vol. 4, 2021, pp. 4–4, doi: 10.17705/1JAIS.00689.
6. Y. Sun, F. Shuyue, and Z. Zuopeng (Justin), "Impression management strategies on enterprise social media platforms: An affordance perspective," Int. J. Inf. Manag., 2021, doi: 10.1016/J.IJINFOMGT.2021.102359.
7. N. Helberger, "The political power of platforms: How current attempts to regulate misinformation amplify opinion power," Digit. Journalism, vol. 6, pp. 842–854, 2020, doi: 10.1080/21670811.2020.1773888.
8. T. C. Schelling, "Dynamic models of segregation," J. Math. Sociol., vol. 1, no. 2, pp. 143–186, 1971, doi: [insert DOI here].
9. J. McMullan, "A new understanding of ‘New Media’: Online platforms as digital mediums," Converg. Int. J. Res. New Media Technol., vol. 2, pp. 287–301, 2020, doi: 10.1177/1354856517738159.
10. University of Oslo, "What does Facebook ‘afford’ do-it-yourself musicians? Considering social media affordances as sites of contestation," Media, Cult. Soc., vol. 2, pp. 277–292, 2020, doi: 10.1177/0163443719853498.
11. Y. Sun, X. Zhou, J. Anand, R. Shang An, and F. Hu, "The impact of enterprise social media platforms on knowledge sharing: An affordance lens perspective," J. Enterp. Inf. Manag., vol. 2, pp. 233–250, 2019, doi: 10.1108/jeim-10-2018-0232.
12. N. Freiling, N. M. Krause, D. A. Scheufele, and D. Brossard, "Believing and sharing misinformation, fact-checks, and accurate information on social media: The role of anxiety during COVID-19," New Media Soc., vol. 1, pp. 141–162, 2023, doi: 10.1177/14614448211011451.
13. S. Zhang, "Exploring how Chinese TV dramas reach global audiences via Viki in the transnational flow of TV content," J. Transcultural Commun., vol. 1, pp. 69–89, 2022, doi: 10.1515/JTC-2022-0014.
14. O. D. Apuke and B. Omar, "Social media affordances and information abundance: Enabling fake news sharing during the COVID-19 health crisis," Health Inform. J., vol. 27, no. 3, pp. 1071–1081, 2021, doi: 10.1177/14604582211021470.
15. B. J. O'Keefe and S. A. McCornack, "Message design logic and message goal structure: Effects on perceptions of message quality in regulative communication situations," Hum. Commun. Res., vol. 14, no. 1, pp. 68–92, 1987, doi: 10.1111/j.1468-2958.1987.tb00122.x.
16. Y. Wu, S. Nambisan, J. Xiao, and K. Xie, "Consumer resource integration and service innovation in social commerce: The role of social media influencers," J. Acad. Mark. Sci., vol. 3, pp. 1–31, 2022, doi: 10.1007/S11747-022-00837-Y.
17. A. H. Eagly and S. Chaiken, "Attitude structure and function," Annu. Rev. Psychol., vol. 49, no. 1, pp. 275–306, 1998.
18. S. W. Sussman and W. S. Siegal, "Informational influence in organizations: An integrated approach to knowledge adoption," Inf. Syst. Res., vol. 14, no. 1, pp. 47–65, 2003, doi: 10.1287/isre.14.1.47.14767.
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