Characterizing communities of hashtag usage on twitter during the 2020 COVID-19 pandemic by multi-view clustering
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(2020) 5:66
Applied Network Science
RESEARCH
Open Access
Characterizing communities of hashtag usage on twitter during the 2020 COVID-19 pandemic by multi-view clustering Iain J. Cruickshank*
and Kathleen M. Carley
*Correspondence: [email protected] CASOS, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA, USA
Abstract The COVID-19 pandemic has produced a flurry of online activity on social media sites. As such, analysis of social media data during the COVID-19 pandemic can produce unique insights into discussion topics and how those topics evolve over the course of the pandemic. In this study, we propose analyzing discussion topics on Twitter by clustering hashtags. In order to obtain high-quality clusters of the Twitter hashtags, we also propose a novel multi-view clustering technique that incorporates multiple different data types that can be used to describe how users interact with hashtags. The results of our multi-view clustering show that there are distinct temporal and topical trends present within COVID-19 twitter discussion. In particular, we find that some topical clusters of hashtags shift over the course of the pandemic, while others are persistent throughout, and that there are distinct temporal trends in hashtag usage. This study is the first to use multi-view clustering to analyze hashtags and the first analysis of the greater trends of discussion occurring online during the COVID-19 pandemic. Keywords: Social media, Clustering, Multi-view data, COVID-19
Introduction At the time of the writing of these words, the world is undergoing a pandemic. This pandemic, which is caused by the SARS-CoV-2 virus and often referred to as the COVID-19 pandemic, has caused immense societal and economic disruption across the world. Since the onset of the COVID-19 pandemic many nations have adopted a social-distancing strategy which has had the unintended consequence of emphasizing and increasing the role of social media in linking people together (Article19 2020; Hussain 2020). Consequently, the study of social media data during the current COVID-19 pandemic can provide unique insights into online social behavior. Thus far, much of the work with COVID-19 social media data has focused on the prevalence and spread of COVID-19 misinformation. There has been less work on understanding what are the important topics of discussion associated with the pandemic and how those discussion topics may change over the course of the pandemic. One social media innovation which can be used to characterize and understand topics of social © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commo
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