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Tracks citizen concerns during COVID-19 using public sentiment analysis from Twitter data, indicating emotional responses.
COVID-19, the disease caused by the Corona Virus, started from Wuhan, China, in late December 2019, and quickly swept the Asian countries with confirmed cases and deaths. Within two and half months, it started spreading to European countries, and to the US, triggering the pandemic declaration by WHO. Governments around the globe have declared a public health crisis in specific regions and nationwide, with drastic measures taken to contain the spread of the disease. Citizens in this public health crisis are going through a wide range of emotions, such as disbelief, shock, concerns about health, fear about food supplies, anxiety, panic, etc., through directly and viscerally experiencing the disease spreading. We present an approach to measure and monitor citizens’ concern levels using public sentiments in Twitter data. Our approach shows temporal and geographic spread of citizens’ concerns during the COVID-19 public health crisis.
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Chun et al. (2020) studied this question.
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