Inferring models of opinion dynamics from aggregated jury data
PLoS ONE, ISSN: 1932-6203, Vol: 14, Issue: 7, Page: e0218312
2019
- 6Citations
- 15Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations6
- Citation Indexes6
- CrossRef5
- Captures15
- Readers15
- 15
Article Description
Jury deliberations provide a quintessential example of collective decision-making, but few studies have probed the available data to explore how juries reach verdicts. We examine how features of jury dynamics can be better understood from the joint distribution of final votes and deliberation time. To do this, we fit several different decision-making models to jury datasets from different places and times. In our best-fit model, jurors influence each other and have an increasing tendency to stick to their opinion of the defendant’s guilt or innocence. We also show that this model can explain spikes in mean deliberation times when juries are hung, sub-linear scaling between mean deliberation times and trial duration, and unexpected final vote and deliberation time distributions. Our findings suggest that both stubbornness and herding play an important role in collective decision-making, providing a nuanced insight into how juries reach verdicts, and more generally, how group decisions emerge.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85069263028&origin=inward; http://dx.doi.org/10.1371/journal.pone.0218312; http://www.ncbi.nlm.nih.gov/pubmed/31260463; https://dx.plos.org/10.1371/journal.pone.0218312; https://dx.doi.org/10.1371/journal.pone.0218312; https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0218312
Public Library of Science (PLoS)
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