How Have We Reacted To The COVID-19 Pandemic? Analyzing Changing Indian Emotions Through The Lens of Twitter
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2020
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Abstract
Since its outbreak, the ongoing COVID-19 pandemic has caused unprecedented
losses to human lives and economies around the world. As of 18th July 2020, the
World Health Organization (WHO) has reported more than 13 million confirmed
cases including close to 600,000 deaths across 216 countries and territories.
Despite several government measures, India has gradually moved up the ranks to
become the third worst-hit nation by the pandemic after the US and Brazil, thus
causing widespread anxiety and fear among her citizens. As majority of the
world's population continues to remain confined to their homes, more and more
people have started relying on social media platforms such as Twitter for
expressing their feelings and attitudes towards various aspects of the
pandemic. With rising concerns of mental well-being, it becomes imperative to
analyze the dynamics of public affect in order to anticipate any potential
threats and take precautionary measures. Since affective states of human mind
are more nuanced than meager binary sentiments, here we propose a deep
learning-based system to identify people's emotions from their tweets. We
achieve competitive results on two benchmark datasets for multi-label emotion
classification. We then use our system to analyze the evolution of emotional
responses among Indians as the pandemic continues to spread its wings. We also
study the development of salient factors contributing towards the changes in
attitudes over time. Finally, we discuss directions to further improve our work
and hope that our analysis can aid in better public health monitoring.
| Reference Key |
dasgupta2020how
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| Authors | Rajdeep Mukherjee; Sriyash Poddar; Atharva Naik; Soham Dasgupta |
| Journal | arXiv |
| Year | 2020 |
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