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Covid-19 Public Sentiment Analysis for Indian Tweets Classification

arXiv 2308.06241 ↗First posted 1 Aug 2023cs.CL cs.SIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 2 of its 23 references that are in the map. First posted on arXiv 1 Aug 2023.

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References · 2

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020COVID-19 Public Sentiment Insights and Machine Learning for Tweets Classificationcited by 11

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