Sentiment Analysis of Diabetes Patients’ Experiences Using Machine Learning Techniques

Abstract

Diabetes is a long-term medical disorder that affects blood sugar levels and can cause a variety of related issues, such as heart disease, kidney damage, nerve damage, eye damage and skin ailments. The impact of diabetes on patients' emotional sentiment has not been thoroughly studied, creating a gap in current knowledge on the potential psychological consequences of the disease. This study explores the connection between emotional sentiment and diabetes in an effort to close this knowledge gap. During this study, 215 online forum posts, including patient experiences, problems, routines, and suggestions, were analyzed using two widely used sentiment analysis models, TextBlob and Vader, to investigate whether diabetes affects patients' emotional state. The overall results indicate that diabetes may affect the sentiments of diabetic patients, as observed in their experiences, problems, and suggestions shared as posts on online discussion forums. However, it cannot be conclusively concluded that diabetes always has a significant and directly adverse impact on the sentiments and emotions of diabetic patients. To ascertain whether there is a link between emotions and diabetes, additional in-depth study on the sentiment analysis of patient experiences with diabetes is required, and to identify the specific circumstances under which this association may exist.