The Influence of Online Discourse Tone on Public Perception of the Affordable Housing Program (AHP)

Authors

  • Walumasi Joseph Sumba Africa International University, Kenya
  • Patrick Kasyula Africa International University, Kenya
  • Godfrey Mwamba Tshibangu Africa International University, Kenya

DOI:

https://doi.org/10.70619/vol6iss2pp1-13-831

Keywords:

Online discourse, discourse tone, public perception, Affordable Housing Program, social media, framing theory, social influence theory, sentiment analysis, public policy, Kenya

Abstract

This study examines how the tone of online discourse influences public perception of Kenya’s Affordable Housing Program (AHP) within rapidly expanding social media ecosystems. Drawing on Framing Theory and Social Influence Theory, the research investigates how emotionally charged and socially reinforced narratives shape citizen attitudes toward public policy. The study utilized a quantitative descriptive-correlational design, based on data collected among 362 social media users in Nairobi, Mombasa, Kisumu, and Nakuru counties. Exposure to AHP-related material, perceived tone of discourse, and the way the people were perceived were measured using structured questionnaires and analysed using SPSS. Results indicate that online discussion about the AHP is mostly neutral to moderately negative in nature, and is characterized by skepticism, criticism, and mixed framing. The people's attitudes towards the program also indicate conservative, two-sided views. Inferential statistics, such as ANOVA, demonstrate a statistically significant relationship between discourse tone and attitudes toward the show (p < 0.001), indicating that the more positive or balanced the discourse, the more positive the attitude toward the show. The findings highlight the potent nature of social media in not only reflecting but also actively shaping people's opinions through framing and peer influence processes. The success of policy implementation is not only related to implementation outcomes but also to the tone and format of online communication. It suggests that policymakers should be able to employ proactive communication strategies, engage with online stories, and take action on misinformation to increase the level of trust and legitimacy of the policy among the people.

Author Biographies

Walumasi Joseph Sumba, Africa International University, Kenya

Public Policy and Administration

Patrick Kasyula, Africa International University, Kenya

School of Business and Economics

Godfrey Mwamba Tshibangu, Africa International University, Kenya

School of Business and Economics

References

Adagala, N. A., Mugubi, J., & Kiilu, T. K. (2026). Narratives That Sway: Thematic Framing and Its Influence on Voter Perceptions in Kenya's 2022 Presidential Campaign. Journal of Popular Education in Africa, 10(3), 60-74.

Afyare, A., & Orey, M. A. H. (2025). The Influence of Social Media on Political Discourse and Public Opinion. Architecture Image Studies, 6(3), 1634-1667. https://doi.org/10.62754/ais.v6i3.506

Ahmed, W., & Lugovic, S. (2019). Social media analytics: analysis and visualisation of news diffusion using NodeXL. Online Information Review, 43(1), 149-160. https://doi.org/10.1108/OIR-03-2018-0093

Al-Omoush, K. S., Garrido, R., & Canero, J. (2023). The impact of government use of social media and social media contradictions on trust in government and citizens’ attitudes in times of crisis. Journal of Business Research, 159, 113748. https://doi.org/10.1016/j.jbusres.2023.113748

Benkele, E., Mweemba, B., & Sikalumbi, D. A. (2025). Bridging the Digital Divide: Zambia’s Emerging Tech Frontier. Journal of Business and Economics in 4IR, 1(1), 1-18. https://orcid.org/0000-0003-2882-5517

Dharta, F. Y. (2024). The Influence of Mass Media on Public Opinion Formation: Comparative Analysis of News Framing Techniques. The Journal of Academic Science, 1(2), 43-52. https://doi.org/10.59613/xmby5m53

Galster, G., & Lee, K. O. (2021). Housing affordability: A framing, synthesis of research and policy, and future directions. International Journal of Urban Sciences, 25(sup1), 7-58. https://doi.org/10.1080/12265934.2020.1713864

Groshek, J., & Al-Rawi, A. (2013). Public sentiment and critical framing in social media content during the 2012 US presidential campaign. Social Science Computer Review, 31(5), 563-576. https://doi.org/10.1177/0894439313490401

Gulzar, S. (2023). The role of media in shaping public opinion and social discourse. Contemporary Journal of Social Science Review, 1(1), 30-40.

Güran, M. S., & Özarslan, H. (2022). Framing theory in the age of social media. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (48), 446-457. https://doi.org/10.52642/susbed.1142562

Hanitzsch, T., Hanusch, F., & Lauerer, C. (2016). Setting the agenda, influencing public opinion, and advocating for social change: Determinants of journalistic interventionism in 21 countries. Journalism Studies, 17(1), 1-20. https://doi.org/10.1080/1461670X.2014.959815

Hilbert, M., Vásquez, J., Halpern, D., Valenzuela, S., & Arriagada, E. (2017). One step, two step, network step? Complementary perspectives on communication flows in Twittered citizen protests. Social Science Computer Review, 35(4), 444-461. https://doi.org/10.1177/0894439316639561

Leong, A. D. (2024). Framing in the social media era: Socio-psychological mechanisms underlying online public opinion of cultured meat. New Media & Society, 26(8), 4471-4489. https://doi.org/10.1177/14614448221122211

Lewis, J., Pond, P., Cameron, R., & Lewis, B. (2019). Social cohesion, Twitter and far-right politics in Australia: Diversity in the democratic mediasphere. European Journal of Cultural Studies, 22(5-6), 958-978. https://doi.org/10.1177/1367549419833035

Mendelsohn, J., Budak, C., & Jurgens, D. (2021, June). Modeling framing in immigration discourse on social media. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (pp. 2219-2263).

Ocal, A., & Crowston, K. (2024). Framing and feelings on social media: the futures of work and intelligent machines. Information Technology & People, 37(7), 2462-2488. https://doi.org/10.1108/ITP-01-2023-0049

Puschmann, C., & Powell, A. (2018). Turning words into consumer preferences: How sentiment analysis is framed in research and the news media. SocialMedia+ Society, 4(3), 2056305118797724. https://doi.org/10.1177/2056305118797724

Sam, C. H. (2019). Shaping discourse through social media: Using Foucauldian discourse analysis to explore the narratives that influence educational policy. American Behavioral Scientist, 63(3), 333-350. https://doi.org/10.1177/0002764218820565

Sussman, K. L., Atkinson, L., Anderson, J., Williamson, L., Upshaw, S., & Ntang Beb, J. L. (2026). Moral Framing in AI-Mediated Communication: Exploration of LLM Effects on Engagement Patterns Among Black Americans. Journal of Interactive Advertising, 26(1), 18-33. https://doi.org/10.1080/15252019.2025.2576174

Yamane, T. (1973). Statistics: An introductory analysis.

Yantseva, V. (2020). Migration discourse in Sweden: Frames and sentiments in mainstream and social media. Social Media+ Society, 6(4), 2056305120981059. https://doi.org/10.1177/2056305120981059

Downloads

Published

2026-06-08

How to Cite

Sumba, W. J. ., Kasyula, P. ., & Tshibangu, G. M. . (2026). The Influence of Online Discourse Tone on Public Perception of the Affordable Housing Program (AHP). Journal of Public Policy and Governance, 6(2), 1–13. https://doi.org/10.70619/vol6iss2pp1-13-831

Issue

Section

Articles