Journal Article

Aspect-Based Sentiment Analysis of Online Reviews for Business Intelligence

Jain, Abha, Bansal, Ankita, Tomar, Siddharth

2022

Overview

COVID-19 pandemic has affected the patients to a large extent who are in immediate need of medical care. Now-a-days people rely on online reviews shared on review websites to gather information about hospitals like the availability of beds, availability of ventilators etc. However, these reviews are large in number and unstructured which makes it difficult to interpret them. Hence, the authors have proposed a methodology that will apply an aspect based sentiment analysis on the reviews to gain meaningful insights of the hospital based on different aspects like doctor, staff, facilities etc. For the purpose of empirical validation, a total of 26,071 reviews pertaining to 325 hospitals were scrapped. The authors concluded that the study can be useful for patients as it helps them to select the hospital which best suits them. The study also helps hospital administration to improve the current services according to needs of the patients.

• Publisher: IGI Global
• Subject: Availability / Business intelligence / Computational linguistics / Coronaviruses / COVID-19 / Data mining / Empirical analysis / Epidemics / Health care / Hospitals / Information management / Information services / Keywords / Language / Language processing / Medical advice systems / Medical research / Medicine, Experimental / Natural language interfaces / Natural language processing / Online information services / Online services / Pandemics / Patients / Ratings & rankings / Sentiment analysis / United States / Ventilators