@inproceedings{jang-etal-2020-exploratory,
    title = "Exploratory Analysis of {COVID}-19 Related Tweets in {N}orth {A}merica to Inform Public Health Institutes",
    author = "Jang, Hyeju  and
      Rempel, Emily  and
      Carenini, Giuseppe  and
      Janjua, Naveed",
    editor = "Verspoor, Karin  and
      Cohen, Kevin Bretonnel  and
      Conway, Michael  and
      de Bruijn, Berry  and
      Dredze, Mark  and
      Mihalcea, Rada  and
      Wallace, Byron",
    booktitle = "Proceedings of the 1st Workshop on {NLP} for {COVID}-19 (Part 2) at {EMNLP} 2020",
    month = dec,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/Add-Cong-Liu-Florida-Atlantic-University-author-id/2020.nlpcovid19-2.18/",
    doi = "10.18653/v1/2020.nlpcovid19-2.18",
    abstract = "Social media is a rich source where we can learn about people`s reactions to social issues. As COVID-19 has significantly impacted on people`s lives, it is essential to capture how people react to public health interventions and understand their concerns. In this paper, we aim to investigate people`s reactions and concerns about COVID-19 in North America, especially focusing on Canada. We analyze COVID-19 related tweets using topic modeling and aspect-based sentiment analysis, and interpret the results with public health experts. We compare timeline of topics discussed with timing of implementation of public health interventions for COVID-19. We also examine people`s sentiment about COVID-19 related issues. We discuss how the results can be helpful for public health agencies when designing a policy for new interventions. Our work shows how Natural Language Processing (NLP) techniques could be applied to public health questions with domain expert involvement."
}