A Review on Sentiment Analysis of Twitter data for Diabetes Classification and Prediction

• Published in: 2022 Seventh International Conference on Parallel, Distributed and Grid Computing (PDGC) pp. 693 - 698
• Main Authors: Akhila, Amudala Meghana Shree, Gayathri, Chitluri, Srinivas, B., Devi, B.S. Kiruthika
• Format: Conference Proceeding
• Language: English
• Published: IEEE 25-11-2022
• Subjects: Blogs; deep learning; Industries; Machine learning; Machine learning algorithms; natural language processing; Oral communication; Sentiment analysis; Social networking (online); twitter
• ISBN: 9781665454001; 1665454008
• ISSN: 2573-3079
• DOI: 10.1109/PDGC56933.2022.10053169

Data mining based on Twitter data can be used to analyses and draw meaningful information from the tweets. In order to convey your innermost thoughts and feelings about life, you might use the sentiment keyword. Sentiment analysis is carried out to provide insights from online conversations about a company's products, brands, and services. Identifying and classifying emotions in written texts is possible using advanced machine learning algorithms. Sentiment analysis has its impact in the field of the medical industry. Based on the tweets, the disease can be categorized and predicted. People can be made aware of the risk, and it provides an opportunity for early diagnosis. This article discusses several machine learning and natural language processing algorithms in the field of sentiment analysis based on Twitter tweets. The various existing systems are discussed in detail and their impact on detection and prediction of diabetes is highlighted.