Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
41 tokens/sec
GPT-4o
59 tokens/sec
Gemini 2.5 Pro Pro
41 tokens/sec
o3 Pro
7 tokens/sec
GPT-4.1 Pro
50 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Exploratory Analysis of COVID-19 Related Tweets in North America to Inform Public Health Institutes (2007.02452v1)

Published 5 Jul 2020 in cs.CL, cs.CY, and cs.SI

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 NLP techniques could be applied to public health questions with domain expert involvement.

User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (4)
  1. Hyeju Jang (7 papers)
  2. Emily Rempel (1 paper)
  3. Giuseppe Carenini (52 papers)
  4. Naveed Janjua (1 paper)
Citations (18)