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Title

Analysis of Bangladeshi People's Emotion during Covid-19 in Social Media Using Deep Learning

Author

Md. Sabbir Alam Pran, Md. Rafiuzzaman Bhuiyan, Sheikh Abujar, Syed Akhter Hossain,

Email

aktarhossain@daffodilvarsity.edu.bd

Abstract

World is passing through a very uncertain circumstance as Coronavirus becoming a great threat. Staying in home is the best solution now to be safe. People are now passing their most of the time in social platform. They're reacting in public posts, news, articles and also commenting there. And a persons comment can talk about his sentiment. Emotion exploration is a very famous topic in the field of data mining. Lots of work have been done yet. In this piece of research, Bangladeshi people's comments on several Facebook news post related to coronavirus have been analyzed to observe the sentiment of them toward this situation. Using three classes investigation have been done on their emotions. which are Analytical, Depressed, Angry. The data set was developed in Bangla language. Several deep learning algorithms have been applied and found the maximum accuracy in CNN 97.24% and in LSTM 95.33%. Result shows that most people commented analytically. The outcome draw up the public psychology of Bangladesh toward the pandemic.

Keywords

covid-19 , sentiment analysis , social media , Bangladesh , epidemic , coronavirus , deep learning , facebook

Journal or Conference Name

11th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2020

Publication Year

2020

Indexing

scopus