SENTIMENT ANALYSIS ON COVID-19 RELATED TWEETS

Abstract

1. Introduction COVID-19[1] is a pandemic going on during the current time. COVID-19 poses a new challenge to humankind. Meanwhile, It is essential to know what the majority of people thinking about this pandemic. Sentiment analysis[2] is a widespread technique applied in field of marketing, customer feedback and consumer research. This project performs sentiment analysis on COVID-19 related tweets[3] and getting some higher idea about people's sentiment toward pandemic. After performing sentimental analysis on COVID-19 related tweets, this project also draws some interesting findings and conclusions in the last section. Performing sentiment analysis on social media data like tweets, Facebook comments are challenging task for some reasons .1) Due to high volume, data may or may not be in csv, excel ,or other text-rich formats. Performing operations on data needs 2) To draw human sentiment from raw text itself complex task for a machine. However, recently there are advanced deep learning based methods available for performing such a complex task. For example, Answering the question by chatbot or auto-compilation of a statement in email.[4]. This project takes NLP(Natural Language Processing) approach with the help of Google's pre-trained deep neural network called BERT[5] for identifying sentiment from raw text data. The layers of deep neural network implemented in PyTorch[6].