This repository is a collection of the latest sentiment analysis related research work for the COVID-19 pandemic. Hope that the collection of research work can provide insight to authorities or governments to consider the potential mental health issues of people when making different decisions, like lock down, social distancing, quarantine, etc.
[notice] This collection will be updated intermittently.
- Examination of Community Sentiment Dynamics Due to Covid-19 Pandemic: A Case Study from Australia, J. Zhou et al. [pdf]
- Detecting Topic and Sentiment Dynamics Due to COVID-19 Pandemic Using Social Media, Y. Hui et al. [pdf]
- Detecting Community Depression Dynamics Due to COVID-19 Pandemic in Australia, J. Zhou et al. [pdf]
- Twitter Sentiment Analysis during COVID-19 Outbreak, Akash D Dubey. [link]
- Sentiment analysis of Social Media Response on the Covid19 outbreak, M. Bhat et al. [link]
- Sentiment analysis of nationwide lockdown due to COVID 19 outbreak: Evidence from India, G. Barkur et al. [link]
- Measuring Emotions in the COVID-19 Real World Worry Dataset, B. Kleinberg [pdf]
- Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study, A. Alrazaq et al. [link]
- COVID-19 Public Sentiment Insights and Machine Learning for Tweets Classification, J Samuel [pdf]
- Sentiment Analysis of Filipinos and Effects of Extreme Community Quarantine Due to Coronavirus (COVID-19) Pandemic, C. Pastor et al. [link].
- News Sentiment in the Time of COVID-19, S. R. Buckman et al. [pdf]
- In the Eyes of the Beholder: Sentiment and Topic Analyses on Social Media Use of Neutral and Controversial Terms for COVID-19 [pdf]
- Deep Sentiment Classification and Topic Discovery on Novel Coronavirus or COVID-19 Online Discussions: NLP Using LSTM Recurrent Neural Network Approach, H. Jelodar et al. [pdf].
- COVID-19 pandemic: a sentiment analysis, A. Kumar et al. [link]