الخوارزميات الرقمية وفقاعات المعلومات في تشكيل النقاش العام داخل الفضاء الرقمي الليبي

Mohamed Al-Menfi; Mohamed El Bakkai

doi:10.26629/uzfaj.2026.28

Authors

Mohamed Al-Menfi University of Benghazi https://orcid.org/0009-0001-8378-7923
Mohamed El Bakkai جامعة بنغازي https://orcid.org/0009-0003-0617-9662

DOI:

https://doi.org/10.26629/uzfaj.2026.28

Keywords:

Digital News Trust, Media Credibility, Social Media Platforms, Libyan Audience, Digital News.

Abstract

This study aims to analyze the role of digital algorithms and filter bubbles in shaping public debate within the Libyan digital sphere by exploring how algorithmic personalization mechanisms influence content flow and reshape patterns of exposure and interaction across social media platforms.

The study adopted a descriptive-analytical approach and employed an electronic questionnaire as the primary data collection tool. Data were collected from a purposive sample of (150) participants, including opinion leaders, members of the National Reconciliation Committee, and community actors in Benghazi, as influential actors in shaping public debate within the digital environment. Data analysis relied on several statistical techniques, including means, standard deviations, and Pearson correlation to examine relationships among the study variables. The findings revealed a high level of awareness regarding the role of algorithms in organizing and prioritizing content, along with a high level of selective exposure to information, reflecting the emergence of homogeneous information environments associated with filter bubbles, The results also showed that algorithms play a significant role in directing public debate, amplifying certain issues while reducing the visibility of others, in addition to increasing interaction with public issues across digital platforms.

The hypothesis testing results indicated statistically significant relationships among the study variables, demonstrating that awareness of algorithmic mechanisms is associated with patterns of selective exposure and interaction within the digital environment. These findings suggest that awareness of platform mechanisms does not necessarily reduce their influence on shaping exposure and engagement patterns. The study concludes that algorithms are no longer merely technical tools for organizing content; rather, they have become a structural actor contributing to shaping public debate within the Libyan digital sphere through restructuring information flows and influencing patterns of digital interaction.

References

بسومي، نداء، (2025)، تحولات نظرية حراسة البوابة في البيئة الرقمية في ظل الخوارزميات ومنصات التواصل الاجتماعي، مجلة جامعة القدس المفتوحة للبحوث والدراسات.

https://repository.aaup.edu/jspui/bitstream/123456789/3111/1/

2- Garajamirli, A. (2025). Algorithmic gatekeeping and democratic communication: Who decides what the public sees? Journal of Media and Communication Studies.

https://eu-opensci.org/index.php/media/article/view/554/206?utm_source=chatgpt.com

3- Areeb, Z., Ali, R., & Hassan, A. (2023). Filter bubbles in recommender systems: Fact or fallacy. arXiv.

https://arxiv.org/pdf/2307.01221

4- Richmond, J., & Tuovinen, J. (2023). Evaluating the use of user content feed swapping for counteracting filter bubbles. CEUR Workshop Proceedings.

https://ceur-ws.org/Vol-3582/FP_04.pdf

5- Newman, N., Fletcher, R., Robertson, C. T., Eddy, K., & Nielsen, R. K. (2023). Reuters Institute digital news report 2023. Reuters Institute for the Study of Journalism.

6- Leysen, J., Geerts, A., & De Moor, K. (2022). What are filter bubbles really? A review of the conceptual and empirical work. University of Antwerp.

https://adrem.uantwerpen.be/bibrem/pubs/bubbles.pdf

7-Cinelli, M., Morales, G. D. F., Galeazzi, A., Quattrociocchi, W., & Starnini, M. (2021). The echo chamber effect on social media. Proceedings of the National Academy of Sciences, 118(9), e2023301118.

https://www.pnas.org/doi/10.1073/pnas.2023301118?utm_source=chatgpt.com

8-Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Sage Publications.

9- Field, A. (2018). Discovering statistics using IBM SPSS statistics (5th ed.). Sage Publications.

https://archive.org/details/discoveringstati0000fiel

10- DeVellis, R. F. (2017). Scale development: Theory and applications (4th ed.). Sage Publications

https://archive.org/details/scaledevelopment0000deve

11- Bryman, A. (2016). Social research methods (5th ed.). Oxford University Press

https://archive.org/details/socialresearchme0000brym

12- Papacharissi, Z. (2015). Affective publics: Sentiment, technology, and politics. Oxford University Press.

https://academic.oup.com/book/5670

13- Fowler, F. J. (2014). Survey research methods (5th ed.). Sage Publications.

https://archive.org/details/surveyresearchme0000fowl

14- Gillespie, T. (2014). The relevance of algorithms. In T. Gillespie, P. Boczkowski, & K. Foot (Eds.), Media technologies: Essays on communication, materiality, and society. MIT Press.

15- Wimmer, R. D., & Dominick, J. R. (2014). Mass media research: An introduction (10th ed.). Cengage Learning.

https://archive.org/details/massmediaresearc0000wimm

16- Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach’s alpha. International Journal of Medical Education, 2, 53–55.

https://pmc.ncbi.nlm.nih.gov/articles/PMC4205511/

17- Pariser, E. (2011). The filter bubble: What the Internet is hiding from you. Penguin Press.

18- Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59–68.

https://www.sciencedirect.com/science/article/abs/pii/S0007681309001232

19- Katz, E., & Lazarsfeld, P. F. (1955). Personal influence: The part played by people in the flow of mass communications. Free Press.

https://archive.org/details/personalinfluenc0000katz

20- Habermas, J. (1989). The structural transformation of the public sphere. MIT Press.

21- Likert, R. (1932). A technique for the measurement of attitudes. Archives of Psychology, 140, 1–55.

https://legacy.voteview.com/pdf/Likert_1932.pdf