Covid-19 Public Sentiment Analysis for Indian Tweets Classification
This work addresses sentiment analysis for public health monitoring in India, but it appears incremental as it applies standard methods to new data without novel contributions.
The paper tackled sentiment analysis of COVID-19 tweets from India by extracting Twitter data and applying sentiment analysis queries to classify opinions as positive, negative, or neutral, but did not report specific results or numbers.
When any extraordinary event takes place in the world wide area, it is the social media that acts as the fastest carrier of the news along with the consequences dealt with that event. One can gather much information through social networks regarding the sentiments, behavior, and opinions of the people. In this paper, we focus mainly on sentiment analysis of twitter data of India which comprises of COVID-19 tweets. We show how Twitter data has been extracted and then run sentimental analysis queries on it. This is helpful to analyze the information in the tweets where opinions are highly unstructured, heterogeneous, and are either positive or negative or neutral in some cases.