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arXiv · 2008.05900

An Exploratory Study of COVID-19 Information on Twitter in the Greater Region

Ninghan Chen·Zhiqiang Zhong·Jun Pang
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Abstract

The outbreak of the COVID-19 leads to a burst of information in major online social networks (OSNs). Facing this constantly changing situation, OSNs have become an essential platform for people expressing opinions and seeking up-to-the-minute information. Thus, discussions on OSNs may become a reflection of reality. This paper aims to figure out the distinctive characteristics of the Greater Region (GR) through conducting a data-driven exploratory study of Twitter COVID-19 information in the GR and related countries using machine learning and representation learning methods. We find that tweets volume and COVID-19 cases in GR and related countries are correlated, but this correlation only exists in a particular period of the pandemic. Moreover, we plot the changing of topics in each country and region from 2020-01-22 to 2020-06-05, figuring out the main differences between GR and related countries.

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Ninghan Chen, Zhiqiang Zhong, Jun Pang. 2020-12-02. An Exploratory Study of COVID-19 Information on Twitter in the Greater Region. https://arxiv.org/abs/2008.05900

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