Loso Judijanto

Cryptocurrency and Behavioral Finance: Co-Word Analysis and Research Evolution

Introduction

Cryptocurrency and behavioral finance: co-word analysis and research evolution. Explore the evolving intersection of cryptocurrency and behavioral finance through co-word analysis. Uncover dominant research themes, investor sentiment, and future trends in digital financial markets.

Abstract

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.

Review

This study presents a timely and relevant exploration into the dynamic interface between cryptocurrency and behavioral finance. Employing a scientometric methodology, specifically co-word analysis, the authors meticulously map the intellectual structure and evolution of this interdisciplinary field. By analyzing publications indexed in the Scopus database from 2010 to what appears to be a forward-looking scope extending to 2025, the research aims to identify dominant themes, key intellectual structures, and emerging trends, thereby providing a comprehensive overview of its development and trajectory. A significant strength of this work lies in its clear articulation of the field's progression. The study effectively demonstrates an early research emphasis on foundational behavioral finance concepts such as investor sentiment, market efficiency, and biases within the context of initial cryptocurrency trading. Crucially, it highlights a notable maturation, characterized by the integration of advanced methodologies like machine learning, sentiment analysis, and portfolio optimization. This convergence underscores a powerful synthesis of traditional behavioral theories with modern data-driven techniques. Furthermore, the mapping of global collaboration patterns robustly illustrates the increasingly international and interdisciplinary nature of knowledge production, offering valuable insights into the social dynamics of research within this domain. These findings are posited as highly beneficial for a diverse audience, including researchers, practitioners, and policymakers, by pinpointing key research clusters and practical implications. While the chosen scientometric approach effectively delineates the research landscape, the abstract’s ambitious claim of contributing to "theoretical integration" and laying "groundwork for more nuanced, data-informed behavioral research" would benefit from the full paper illustrating how co-word analysis directly facilitates this. Future iterations or extensions of this work could potentially delve deeper into the qualitative aspects of the identified clusters, exploring the specific theoretical frameworks being integrated and the precise nature of their synthesis. Nonetheless, the study provides a robust and valuable foundational resource, charting the evolution from nascent behavioral inquiries to sophisticated, data-driven insights in digital financial markets. It effectively sets the stage for future research to explore the causal mechanisms and practical implications of these emerging trends, thereby advancing our understanding of digital financial behavior.

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