Digital Personas in AI-Assisted Qualitative Research Chapter in Scopus uri icon

abstract

  • Qualitative researchers face substantial human and technological challenges when analysing extensive textual data from platforms such as X (formerly Twitter) and other digital spaces where large-scale human interactions unfold. These limitations hinder the ability to derive nuanced insights from large-scale social interactions, which is crucial for informed decision-making in various domains. Addressing these challenges is vital for improving the depth and accuracy of qualitative analyses, facilitating more effective integration of diverse disciplinary insights into practical applications. While literature acknowledges these difficulties, it often lacks methodologies to manage the massive data inherent in digital communications. The contribution of this paper lies in its philosophical and methodological exploration of artificial intelligence (AI) as a transformative agent in qualitative research. By introducing 'digital personas' as virtual researchers and consolidated embodiments of collective public sentiment, this study explores the relationship between human interpretation and computational analysis, seeking to address fundamental questions about the capacity and philosophical implications of using Large Language Model based AI to synthesise complex human experiences. This paper employs a real-world case study involving millions of interactions on X related to a high-profile academic and ethical case involving a prominent political figure. By analysing this large-scale discourse, the study highlights how digital personas bridge human interpretation and computational analysis, showcasing the role of AI-driven qualitative analysis in fostering more informed, transparent, and accountable discussions in society, ultimately contributing to a more reflective and responsible digital public sphere. © 2025 The Authors.

publication date

  • October 14, 2025