Satisfaction Survey

Satisfaction surveys are used to gauge opinions and experiences, with recent research focusing on improving data analysis and interpretation. Current methods leverage natural language processing (NLP) techniques, including sentiment analysis and opinion mining, to extract meaningful insights from textual responses, and machine learning models, such as tree regression, to predict satisfaction based on various factors like visual access. This work aims to enhance the accuracy and efficiency of survey analysis, leading to more actionable data for improving products, services, and overall user experience across diverse fields, from architecture to mental health interventions.