Collaborative Academic Research Values of AI Text Analysis
(R2023-117265)

AUTHORS

Máté Bollók, Corvinus University of Budapest; Zsófia Molnár, Corvinus University of Budapest; Levente Kökény, Corvinus University of Budapest; Áron Szabó, Corvinus University of Budapest; Tamás Csordás, Corvinus University of Budapest; Dóra Horváth, Corvinus University of Budapest

ABSTRACT

The present paper examines the use of Natural Language Processing (NLP) systems as a collaborative tool in academic research. The authors used a Python-based AI to analyze three research topics and find connections between different fields using NLP exclusively. The demand for such tools arises from the labor-intensive nature of data mining and the limitations of human memory capacity. The study finds that AI-enabled research might provide a time-efficient way for preparing scientific publications. However, the authors believe that the presented AI tool is not advanced enough to replace human intuition and critical thinking in deep academic research, despite its potential benefits in qualitative research.