Factors Influencing the Adoption of Artificial Intelligence Powered Factchecking Chatbots among Internet Users in Ilorin Metropolis
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Date
2026-09
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Abstract
This study examined the factors influencing the adoption of artificial intelligence
powered fact-checking chatbots among internet users in Ilorin metropolis, Kwara State,
Nigeria, applying the Unified Theory of Acceptance and Use of Technology to identify
what drives trust in and adoption of these tools. A quantitative survey design was adopted
and structured questionnaire built around a four-point Likert scale was administered to
400 respondents but later reduced to 399 internet users due to invalid data. Respondents
were selected through purposive and convenience sampling. Data were analysed using
correlation and regression techniques in SPSS version 27. Four hypotheses were tested
individually and were all rejected, confirming that trust, performance expectancy, social
influence and effort expectancy each significantly predict adoption. When the four
constructs were combined in a single regression model, however, only performance
expectancy and social influence retained significant, independent effects on both trust and
adoption, while effort expectancy and facilitating conditions fell away, with performance
expectancy emerging as the strongest predictor overall. The study concluded that
usefulness and social endorsement, rather than ease of use or infrastructure alone, are
what most strongly drive adoption of these tools in this context. It recommended that
developers prioritise transparent, demonstrable accuracy in chatbot design, that factchecking organisations invest in building social visibility for their tools, and that future
studies test the trust-adoption relationship as a formal mediation model using data
collected across a wider geographic area.
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Citation
Mohammed, N. H. & Shaibu, A.J. (2026). Factors Influencing the Adoption of Artificial Intelligence Powered Fact-checking Chatbots among Internet Users in Ilorin Metropolis. Biannual Review of Glorious Vision University, 3 (2) Ogwa, Edo State, Nigeria. https://doi.org/10.5281/zenodo.22104272