Time Series Analysis of Sentiment: A Comparison of the US and UK Coronavirus Subreddits

Martyn Harris, Mark Levene () and Andrius Mudinas ()
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Martyn Harris: Department of Computer Science and Information Systems, Birkbeck, University of London, London WC1E 7HX, UK
Mark Levene: Department of Computer Science and Information Systems, Birkbeck, University of London, London WC1E 7HX, UK
Andrius Mudinas: Department of Computer Science and Information Systems, Birkbeck, University of London, London WC1E 7HX, UK

International Journal of Information Technology & Decision Making (IJITDM), 2024, vol. 23, issue 01, 57-88

Abstract: In this paper, we investigate the dynamics of the social media response on Reddit to the COVID-19 pandemic during its first year (February 2020–2021). The emergence of region-specific subreddits allows us to compare the reactions of individuals posting their opinions on social media about the global pandemic from two perspectives — the UK and the US.In particular, we look at the volume of posts and comments on these two subreddits, and at the sentiment expressed in these posts and comments over time as a measure of the public level of engagement and response. Whilst an analysis of volume allows us to quantify how interested people are about the pandemic as it unfolds, sentiment analysis goes beyond this and informs us about how people respond towards the pandemic based on the textual content in the posts and comments. The research looks to develop a framework for analyzing the social response on Reddit to a large-scale event in terms of the level of engagement measured through post and comment volumes, and opinion measured through an analysis of sentiment applied to the post content. In order to compare the subreddits, we show the trend in the time series through the application of moving average methods. We also show how to identify the lag between time series and align them using cross-correlation. Moreover, once aligned, we apply moving correlations to the time series to measure their degree of correspondence to see if there is a similar response to the pandemic across the two groups (UK and US). The results indicate that both subreddits were posting in high volumes at specific points during the pandemic, and that, despite the generally negative sentiment in the posts and comments, a gradual decrease in negativity leading up to the start of 2021 is observed as measures are put in place by governments and organizations to contain the virus and provide necessary support the affected populations.

Keywords: Time series analysis; NLP; sentiment analysis; machine learning; Reddit (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S0219622023400035

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