Trust in Algorithmically Curated News among Facebook Users in Bangladesh

Algorithmically curated news has become an important part of social media news consumption, particularly on Facebook. Although algorithmic systems increasingly shape users’ exposure to online news, limited research has examined users’ trust in algorithmically curated news within developing countries such as Bangladesh. This study examined the technological and behavioural factors associated with Trust in Algorithmically Curated News among Facebook users in Bangladesh. A quantitative cross-sectional survey was conducted among 230 Facebook users. The study integrated selected constructs from the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Theory of Planned Behaviour (TPB). Data were analysed using descriptive statistics and Pearson correlation analysis. The findings revealed that all seven examined factors had significant positive relationships with Trust in Algorithmically Curated News (p < .001). Attitude Toward Behaviour showed the strongest relationship (r = .699), followed by Social Influence (r = .609) and Effort Expectancy (r = .608). The findings suggest that trust in algorithmically curated news is associated with technological perceptions, social influence, and behavioural evaluations. This study contributes to the literature on algorithmic trust, social media news consumption, and digital communication in emerging media environments.

Algorithmic Trust, Social Media, Facebook, News Consumption

1. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://www.researchgate.net/publication/342077056_The_theory_of_planned_behavior_Frequently_asked_questions [Google Scholar] [Crossref]

2. Datareportal. (2023). Digital 2023: Bangladesh. Datareportal. https://datareportal.com/reports/digital-2023-bangladesh [Google Scholar] [Crossref]

3. Diakopoulos, N. (2020). Computational news discovery: Towards design considerations for editorial orientation algorithms in journalism. Digital Journalism, 8(7), 945–967. https://www.semanticscholar.org/paper/Computational-News-Discovery%3A-Towards-Design-for-in-Diakopoulos/dd609f6355fa51f525f2804df8eaf7ddc2a57142 [Google Scholar] [Crossref]

4. Eslami, M., Rickman, A., Vaccaro, K., Aleyasen, A., Vuong, A., Karahalios, K., Hamilton, K., & Sandvig, C. (2015). “I always assumed that I wasn’t really that close to [her]”: Reasoning about invisible algorithms in news feeds. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 153–162. https://dl.acm.org/doi/10.1145/2702123.2702556 [Google Scholar] [Crossref]

5. Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics (5th ed.). Sage. https://www.scirp.org/reference/referencespapers?referenceid=3504991 [Google Scholar] [Crossref]

6. Metzger, M. J., & Flanagin, A. J. (2013). Credibility and trust of information in online environments: The use of cognitive heuristics. Journal of Pragmatics, 59, 210–220. https://www.sciencedirect.com/science/article/abs/pii/S0378216613001768?via%3Dihub [Google Scholar] [Crossref]

7. Newman, N., Fletcher, R., Robertson, C. T., Eddy, K., & Nielsen, R. K. (2022). Reuters Institute Digital News Report 2022. Reuters Institute for the Study of Journalism. https://reutersinstitute.politics.ox.ac.uk/digital-news-report/2023 [Google Scholar] [Crossref]

8. Pallant, J. (2020). SPSS Survival Manual: A Step by Step Guide to Data Analysis Using IBM SPSS (7th ed.). McGraw-Hill Education. https://www.scirp.org/reference/referencespapers?referenceid=3007539 [Google Scholar] [Crossref]

9. Rader, E., Cotter, K., & Cho, J. (2018). Explanations as mechanisms for supporting algorithmic transparency. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, 1–13. https://dl.acm.org/doi/10.1145/3173574.3173677 [Google Scholar] [Crossref]

10. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://aisel.aisnet.org/jais/vol17/iss5/1/ [Google Scholar] [Crossref]

11. Wardle, C., & Derakhshan, H. (2017). Information disorder: Toward an interdisciplinary framework for research and policy making. Council of Europe. https://www.scirp.org/reference/referencespapers?referenceid=3238110 [Google Scholar] [Crossref]

12. Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. Science, 359(6380), 1146–1151. https://www.science.org/doi/10.1126/science.aap9559 [Google Scholar] [Crossref]

• Social Media and Ghanaian Youth: A Systematic Review of Impacts and Implications
• Social Media Trends and Public Opinion Dynamics in Port Harcourt
• The Impact of Social Media Information in Checkmating Social Injustice and Bad Governance in Nigeria
• The Impact of Image-Based Brand Content on Moroccan Consumers Engagement on Social Media
• Qur’anic Character Model in Enhancing the Quality of Job Satisfaction among the Civil Servants