Evidence map›Paper›PMID 35318589›Full record

ArticleBehavior research methods2023

Quantifying changes in societal optimism from online sentiment.

Calvin Isch, Marijn Ten Thij, Peter M Todd, Johan Bollen

Abstract read
In one paragraph

Article in Behavior research methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Calvin IschCognitive Science Program, Indiana University Bloomington, 1001 E. 10th St., Bloomington, IN, 47405, USA. calvin.isch@gmail.com.ORCID http://orcid.org/0000-0003-1669-0918
Marijn Ten ThijCenter for Social and Biomedical Complexity, Indiana University Bloomington, 1015 E. 11th St., Bloomington, IN, 47408, USA.
Peter M ToddCognitive Science Program, Indiana University Bloomington, 1001 E. 10th St., Bloomington, IN, 47405, USA.
Johan BollenCognitive Science Program, Indiana University Bloomington, 1001 E. 10th St., Bloomington, IN, 47405, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

COVID-19Social MediaAttitudeHumansPandemicsComputational scienceNatural language processingOptimismOptimism curveSentiment analysisSocial MediaSocietal moodSocietal optimismTwitterYield curve inversion

Identifiers

PMID35318589
PMCPMC8939395

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.