Publication Type : Conference Paper
Publisher : Springer Nature Singapore
Source : Lecture Notes in Networks and Systems
Url : https://doi.org/10.1007/978-981-16-7618-5_20
Campus : Amritapuri
School : School of Computing
Year : 2022
Abstract : Coronavirus disease (COVID-19) has adversely affected all walks of human life. The whole world is confronting this deadly virus, and no country in this world remains untouched during this pandemic. There are several online news videos related to COVID-19 that are shared on various online platforms such as YouTube, DailyMotion, and Vimeo. There were several arguments on the genuineness of the contents, people watch them, share them, and most importantly express their views and opinions as comments on those platforms. Analyzing these comments can unearth the patterns hidden in them to study people's responses to videos on COVID-19. This paper proposes a deep learning-based sentiment analysis approach to people's response toward online COVID-19 video news. This work implements different deep learning approaches such as LSTM, Bi-LSTM, CNN, and GRU to classify sentiment from the comments collected from YouTube.
Cite this Research Publication : Milan Varghese, V. S. Anoop, Deep Learning-Based Sentiment Analysis on COVID-19 News Videos, Lecture Notes in Networks and Systems, Springer Nature Singapore, 2022, https://doi.org/10.1007/978-981-16-7618-5_20