Abstract
This study investigates the determinants of cryptocurrency adoption in Nigeria, an emerging economy characterized by a rapidly growing digital population and unique socio-economic landscape. Utilizing a robust machine learning approach, the research integrates various socio-economic factors, including age, income, education, and employment status, with digital literacy levels as key predictors. A dataset collected from a representative sample of Nigerian adults was employed to train and evaluate several classification models, including Logistic Regression, Random Forest, and Gradient Boosting. The Gradient Boosting model consistently outperformed others, achieving an accuracy of 89.2% and an F1-score of 0.88 in predicting adoption. Feature importance analysis revealed that digital literacy, disposable income, age group (18-35), and access to reliable internet connectivity were the most significant drivers of cryptocurrency adoption. These findings underscore the critical role of both foundational digital skills and economic incentives in shaping the uptake of digital financial innovations in emerging markets. The study provides crucial insights for policymakers, fintech innovators, and educators seeking to foster responsible digital inclusion and financial empowerment in regions like Nigeria, by highlighting areas for targeted intervention in digital education and infrastructure development.
