John McCoy
I am an Assistant Professor of Marketing at the Wharton School of the University of Pennsylvania.
At Penn, I'm also affiliated with the Wharton Neuroscience Initiative and Penn's MindCORE hub.
Trained as a computational cognitive scientist, I'm broadly interested in understanding how people think and decide, and using this understanding to solve marketing problems.
I use a combination of behavioral experiments and formal modeling, drawing on ideas and techniques from psychology, economics, marketing, Bayesian statistics, and computer science.
Much of my work relates to some combination of crowd wisdom and forecasting, measuring preferences and beliefs, and semantic cognition and its applications. For more details, see my CV.
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Selected research
A few recent papers
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Aka, A., Bhatia, S., and McCoy, J. "Semantic determinants of memorability", Cognition, 2023
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Bigelow, E., McCoy, J.*, and Ullman, T.*. "Non-Commitment in Mental Imagery", Cognition, 2023 (Press: Scientific American Discover Magazine )
Crowd wisdom (collective-level measurement)
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My collaborators and I have proposed a new solution to extracting wisdom from the crowd: select not the "most popular" answer, but rather the "surprisingly popular" answer. That is, elicit from respondents their own answer and their prediction about the answers of others and select the answer that is more popular than the crowd predicts.
Representative press:
Wall Street Journal, Bloomberg, Quartz,
MIT news, Scientific American, NPR -
In a working paper (to be updated soon), we show how more general versions of the crowd wisdom problem can be tackled by eliciting beliefs, and predictions about the group belief.
Prelec, D., and McCoy, J. "General identifiability of possible world models for crowd wisdom", 2022
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Perhaps the most natural application of crowd wisdom research is to forecasting, and we've surveyed the forecasting literature from perspective of consumer behavior, particularly the complex, interacting roles of people and algorithms.
Individual-level measurement, decision making, and semantic cognition
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Measuring preferences: in a working paper, we apply conjoint analysis across product categories.
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Measuring attitudes: we proposed a method for measuring how people perceive groups or agents different to themselves.
McCoy, J.* and Ullman, T.* “A Minimal Turing Test”, Journal of Experimental Social Psychology, 2018
OSF link with pre-print, data and analysis
Representative press:
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While some of my work has shown that we can measure nuanced information, for example meta-beliefs that aid in crowd-sourcing, people don't always reveal everything that they know. This is, for example, sometimes true of doctors communicating with patients.
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People's imagination can be a source of insight into their models of the world. For example, how people imagine possible (magical!) worlds relates to their intuitive theories of physics
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People also imagine choices involving various kinds of transformative experiences, which we can study from the perspective of metaphysics and cognitive science.
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We examine how people perceive the risk preferences of others, and how people attribute blame.
Graph theory papers
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I have written some papers in graph theory, mostly dealing with paired domination: