Sentiment Analysis in Healthcare: A Methodological Review

Abstract

Social media has both positive and negative impacts on society, affecting social life significantly. Data mining in social media plays a vital role in finding the needs of day-to-day life like buying products, getting medical assistance, ordering food, etc,. Sentiment analysis, a key component of natural language processing (NLP), automatically extracts opinions and emotions from this data to provide insightful information. The rise of online health information and social media has created a rich source of unstructured text data, including patient reviews, social media discussions, and clinical notes. Sentiment analysis in healthcare, applied in the fields of encompassing patient satisfaction analysis, treatment efficacy evaluation, and public health monitoring. This paper gives an overview on sentiment analysis, its types and various methods involved including lexicon – based, Machine Learning, etc., and techniques employed in approaching the healthcare data. The applications and advantages of sentiment analysis in health care sector and highlighting its potential and paving the way for future research directions.