This study explores the evolving intersection between cryptocurrency and behavioral finance through a scientometric approach using co-word analysis. By analyzing publications indexed in the Scopus database from 2010 to 2025, the study identifies dominant research themes, intellectual structures, and emerging trends within this interdisciplinary field. The analysis reveals that early research focused heavily on investor sentiment, market efficiency, and behavioral biases related to bitcoin and cryptocurrency trading. Over time, the literature has expanded to include advanced methodologies such as machine learning, sentiment analysis, and portfolio optimization, highlighting a growing convergence between behavioral theories and data-driven techniques. Furthermore, the study maps global collaboration patterns among authors, institutions, and countries, showing that knowledge production is increasingly international and interdisciplinary. The findings provide valuable insights for researchers, practitioners, and policymakers by highlighting key research clusters, practical implications, and future directions in the study of digital financial behavior. This work contributes to the theoretical integration of behavioral finance and crypto-asset studies and lays the groundwork for more nuanced, data-informed behavioral research in digital markets.
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