Calls for Research at the University of Nariño: Perception Analysis Based on AI-Powered Computational Linguistics

Abstract

This study presents an AI-powered computational linguistics analysis of researchers’ perceptions regarding the calls for research at the University of Nariño. A survey was conducted among 48 researchers, in which they provided open-ended responses about the challenges faced in previous calls for research and suggested improvements to enhance the research system. Using natural language processing (NLP) techniques, the analysis identified recurring themes and sentiments expressed in the responses. The results highlight key areas of difficulty, including administrative barriers, funding allocation, and transparency in evaluation criteria. Additionally, sentiment analysis revealed predominant concerns and potential areas for reform. The findings of this study contribute to an evidence-based improvement plan aimed at optimizing future calls for research at the University of Nariño. The application of AI-driven computational linguistics demonstrates its effectiveness in extracting meaningful insights from unstructured textual data, providing a replicable model for similar institutional evaluations.