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{ "pk": 25822, "title": "Using Ground Truths to Improve Wisdom of the Crowd Estimates", "subtitle": null, "abstract": "In this paper we explore a cognitive modeling approach to aggregating\nindividuals’ estimates of unknown quantities without\nnatural bounds. We carried out two experiments that elicited\nindividuals’ estimates of the population of US metropolitan areas,\nand domestic box office returns for movies. We found\nthat the means of individuals’ responses correlate well with\nthe true sizes, but participants systematically underestimated\nthese values. We formulated a cognitive model that uses the\ntrue values of known items to correct for individuals’ biases,\nand demonstrated that this model can drastically improve predictive\naccuracy. Because our model quantitatively infers individual’s\nbiases on the estimation tasks we were able to examine\nthe distribution of individual biases, and found that there were\nsubstantial between-individual differences in the magnitude of\nthe responses. This work demonstrates how individuals’ biases,\nwhether over- or underestimation, can be corrected using\na cognitive model together with known ground truths", "language": "eng", "license": { "name": "", "short_name": "", "text": null, "url": "" }, "keywords": [ { "word": "wisdom of the crowd; graphical model; hierarchical\nBayesian model; human judgments; individual differences" } ], "section": "Papers", "is_remote": true, "remote_url": "https://escholarship.org/uc/item/8dv3221t", "frozenauthors": [ { "first_name": "Andrew", "middle_name": "", "last_name": "Whalen", "name_suffix": "", "institution": "University of St Andrews", "department": "" }, { "first_name": "Saiwing", "middle_name": "", "last_name": "Yeung", "name_suffix": "", "institution": "Beijing Institute of Technology", "department": "" } ], "date_submitted": null, "date_accepted": null, "date_published": "2015-01-02T03:00:00+09:00", "render_galley": null, "galleys": [ { "label": "PDF", "type": "pdf", "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/25822/galley/15446/download/" } ] }