Evaluating Performance on Covid-19 Tweet Sentiment Analysis Outbreak Using Support Vector Machine

ABSTRACT

Sentiment analysis is a perfect machine learning process to analyze text and returns the text whether in positive or negative. The machine is trained with the emotions in text, then the machine can automatically understand text and predict the sentiment analysis. Sentiment analysis is an information extraction task that gives the result based on users writing emotions such as positive and negative thoughts, feelings. The emotions can be categorized as positive or negative words. Now, natural language processing (NLP) is an upcoming field in machine learning which gives hybrid applications in daily life. For example, the keyword which is taken from the text will undergo for intelligent learning. The output of the NLP algorithm enables sentiment analysis report daily activities. In this paper, we exposed the Covid-19 tweets from social media and did sentiment analysis using support vector machine (SVM). We trained the system using sentiment model and found the emotions from the Covid-19 tweets. Based on the trained system, we found the emotions in terms of negative, positive, and neutral emotions from Covid-19 tweet messages. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.