Work in Progress: Use of Natural Language Processing in the Evaluation of University Satisfaction Level

The aim of this study is to examine the use of NLP in an extensive amount of satisfaction feedback in the process and experience of university students from the engineering faculty. The NLP process used was sentiment analysis, which uses artificial intelligence for the extraction of textual data and can classify it as positive, neutral, and negative. The results of the NLP were compared with the manual analysis of the same feedback, finding differences in the results of both methods. Finally, we conclude that the sentiment analysis method is feasible to implement in the context of measuring student satisfaction, and it can become an effective tool with the possibility of working in real-time to generate useful information for making university decisions.