This paper presents an innovative approach focusing on understanding the nuances of satisfaction in decision-making contexts, especially regarding higher education enrollment. It addresses the limitations of traditional sentiment analysis in capturing the complex spectrum of human emotions by incorporating neutrosophic statistics. Through a comprehensive analysis using R and RStudio, the study systematically codes sentiment analysis results into neutrosophic sets, exploring different coding methods and their effectiveness in reflecting respondents’ satisfaction levels. The findings underscore the significance of including indeterminacy to enhance model predictions, with certain coding approaches and models proving more effective in capturing the subtleties of satisfaction. The comparative analysis reveals that neutrosophic sets, particularly when incorporating indeterminacy, offer a refined lens through which to view and analyze sentiment data, providing deeper insights into the intricate dynamics of satisfaction in decision-making. This comparative analysis also provides insights into the possibilities of combining neutrosophic sets with some of the more conventional methods, which additionally supports the application of neutrosophic sets and encourages further investigation into their integration with existing methodologies.