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Gabriel Recchia

Researcher at University of Cambridge

Publications -  48
Citations -  3105

Gabriel Recchia is an academic researcher from University of Cambridge. The author has contributed to research in topics: Semantic similarity & Risk perception. The author has an hindex of 15, co-authored 44 publications receiving 1580 citations. Previous affiliations of Gabriel Recchia include University of Memphis & Indiana University.

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Risk perceptions of COVID-19 around the world

TL;DR: It is found that although levels of concern are relatively high, they are highest in the UK compared to all other sampled countries, and risk perception correlated significantly with reported adoption of preventative health behaviors in all ten countries.
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Susceptibility to misinformation about COVID-19 around the world

TL;DR: A clear link between susceptibility to misinformation and both vaccine hesitancy and a reduced likelihood to comply with health guidance measures is demonstrated, and interventions which aim to improve critical thinking and trust in science may be a promising avenue for future research.
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More data trumps smarter algorithms: comparing pointwise mutual information with latent semantic analysis.

TL;DR: This work evaluates a simple metric of pointwise mutual information and demonstrates that this metric benefits from training on extremely large amounts of data and correlates more closely with human semantic similarity ratings than do publicly available implementations of several more complex models.
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COVID-19 risk perception: a longitudinal analysis of its predictors and associations with health protective behaviours in the United Kingdom

TL;DR: In this article, the authors present results from five cross-sectional surveys on public risk perception of COVID-19 and its association with health protective behaviours in the UK over a 10-month period.
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The Shape of Action

TL;DR: A detailed comparison of the joint time courses of these variables showed that looking time and physical change were locally maximal at breakpoints and greater for higher level action units than for lower level units, showing that breakpoints are distinct even out of context.