Sentiment Analysis on Social Media during COVID-19

Abstract: Sentiment analysis is the technology under Natural Language Processing and text analysis techniques to identify and extract subjective information from text. Sentiment analysis is used in many applications for recommendation and feedback analysis. Sentiment analysis over Social Media offers organizations and individuals a fast and effective way to monitor the publics' feelings towards them and their competitors. There are several challenges facing the sentiment analysis and evaluation process. These challenges become obstacles in analyzing the accurate meaning of sentiments and detecting the suitable orientation of the expressed sentiment. Sentiment analysis is process of extracting information from the user's opinions. Every person shares his or her information on social network sites, blogs, product review websites. This paper focuses on evaluating the predictions of sentiment classifiers, additional feature extractions with practical results on defining the sentiment analysis of COVID-19 using twitter data. The analyses are based on the machine learning algorithms. This article provides an analysis on how people react to a pandemic outbreak, how much they are aware of the disease and its symptoms, what precautionary measures they are taking. Algorithms for sentiment analysis and the steps involved in it. A brief description of complex sequence-based Neural Network sentiment classifiers.

Keywords: Sentiment Analysis, Machine Learning, Social Media- Twitter.