  Coronavirus disease (COVID-19) pandemic has changed various aspects of
people's lives and behaviors. At this stage, there are no other ways to control
the natural progression of the disease than adopting mitigation strategies such
as wearing masks, watching distance, and washing hands. Moreover, at this time
of social distancing, social media plays a key role in connecting people and
providing a platform for expressing their feelings. In this study, we tap into
social media to surveil the uptake of mitigation and detection strategies, and
capture issues and concerns about the pandemic. In particular, we explore the
research question, "how much can be learned regarding the public uptake of
mitigation strategies and concerns about COVID-19 pandemic by using natural
language processing on Reddit posts?" After extracting COVID-related posts from
the four largest subreddit communities of North Carolina over six months, we
performed NLP-based preprocessing to clean the noisy data. We employed a custom
Named-entity Recognition (NER) system and a Latent Dirichlet Allocation (LDA)
method for topic modeling on a Reddit corpus. We observed that 'mask', 'flu',
and 'testing' are the most prevalent named-entities for "Personal Protective
Equipment", "symptoms", and "testing" categories, respectively. We also
observed that the most discussed topics are related to testing, masks, and
employment. The mitigation measures are the most prevalent theme of discussion
across all subreddits.
