Quantifying changes in societal optimism from online sentiment

Calvin Isch*, Marijn ten Thij, Peter M. Todd, Johan Bollen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Individuals can hold contrasting views about distinct times: for example, dread over tomorrow’s appointment and excitement about next summer’s vacation. Yet, psychological measures of optimism often assess only one time point or ask participants to generalize about their future. Here, we address these limitations by developing the optimism curve, a measure of societal optimism that compares positivity toward different future times that was inspired by the Treasury bond yield curve. By performing sentiment analysis on over 3.5 million tweets that reference 23 future time points (2 days to 30 years), we measured how positivity differs across short-, medium-, and longer-term future references. We found a consistent negative association between positivity and the distance into the future referenced: From August 2017 to February 2020, the long-term future was discussed less positively than the short-term future. During the COVID-19 pandemic, this relationship inverted, indicating declining near-future- but stable distant-future-optimism. Our results demonstrate that individuals hold differentiated attitudes toward the near and distant future that shift in aggregate over time in response to external events. The optimism curve uniquely captures these shifting attitudes and may serve as a useful tool that can expand existing psychometric measures of optimism.

Original languageEnglish
Pages (from-to)176-184
Number of pages9
JournalBehavior Research Methods
Volume55 (2023)
Issue number1
DOIs
Publication statusPublished - 2022

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Computational science
  • Natural language processing
  • Optimism
  • Optimism curve
  • Sentiment analysis
  • Social Media
  • Societal mood
  • Societal optimism
  • Twitter
  • Yield curve inversion

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