COVID-19 Topic Modeling and Visualization

The World Health Organization announced the novel coronavirus (COVID-19) outbreak as a global pandemic on March 11, 2020. To date, this virus has infected over 13 million people worldwide, causing a significant impact on human societies. More than 570,000 people have lost their lives. This study tri...

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Bibliographic Details
Main Authors: Tao, Grace, Miao, Yuan, Ng, Sebastian
Format: Conference Proceeding
Language:English
Subjects:
COVID-19
information visualization
Latent Dirichlet Allocation (LDA)
Organizations
Pandemics
Public healthcare
Resource management
Social networking (online)
topic modeling
Tweets
Viruses (medical)
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Summary:The World Health Organization announced the novel coronavirus (COVID-19) outbreak as a global pandemic on March 11, 2020. To date, this virus has infected over 13 million people worldwide, causing a significant impact on human societies. More than 570,000 people have lost their lives. This study tries to understand the concern and experiences of the general public in this pandemic via social media data analysis. Twitter is a very popular social media platform where people share their ideas and express their views in a timely manner. It is also one of the most comprehensive sources of public conversation. In this work, we collected COVID-19 related Tweets during this pandemic, analyzed the volume, location, frequent words, main topics and people's emotion. We further visualized the evolution of the main topics along with the development of this pandemic. The analysis and visualization can help us to construct a picture of people's concerns and to understand their behaviors. It would also be helpful to the public health systems to devise proper policies to better guide and support the pubic.
ISSN:2375-0138
DOI:10.1109/IV51561.2020.00129