The coronavirus pandemic has taken the world by a storm. People all around the world are affected and hence talking about the same. Although a lot of the news generated post coronavirus in India as well as globally is accurate, there are still an alarming number of highly misinformed pieces of information, which has affected the doctors and social workers battling coronavirus every day. This study brings forth the discrepancy between the popular sentiment among the public and contrasts it with a database of the research articles that have been published in revered journals. The study culminates with an application based on the concept of natural language processing, which can then be used to gain complete insights into any piece of information and validate one’s beliefs and assumptions on the topic. The main benefit of the application is for the media personnel who can validate news using it. The application is recommended for the purpose of news reporting as well as for summarization of the various research papers related to a topic.

Author Name: Shreya Ghai, Bhulakshmi Bonthu

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Keywords: Natural Language Processing, Machine Learning, Limiting Misinformation, Clustering, Topic Modelling, Coronavirus.

ISSN: 0974-1771

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