Social media has become a mainstream channel of communication during the COVID‐19 pandemic. While some studies have been developed on investigating public opinion on social media data regarding COVID‐19 pandemic, there is no study analyzing anti‐quarantine comments on social media. This study has collected and analyzed near 80,000 tweets to understand anti‐quarantine social comments. Using text mining, we found 11 topics representing different issues such as comparing COVID‐19 and flu and health side effects of quarantine. We believe that this study shines a light on public opinion of people who are against quarantine.

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The COVID‐19 outbreak has posed significant threats to international health and the economy. In the absence of treatment for this virus, public health officials asked the public to practice social distancing to reduce the number of physical contacts. However, quantifying social distancing is a challenging task and current methods are based on human movements. We propose a time and cost‐effective approach to measure how people practice social distancing. This study proposes a new method based on utilizing the frequency of hashtags supporting and encouraging social distancing for measuring social distancing. We have identified 18 related hashtags and tracked their trends between Jan and May 2020. Our evaluation results show that there is a strong correlation (p < .05) between our findings and the Google social distancing report.

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