Discovering Psychological Principles by Mining Naturally Occurring Data Sets

Goldstone, R. L., & Lupyan, G. (2016).  Harvesting naturally occurring data to reveal principles of cognitionTopics in Cognitive Science, 8, 548-568.

The very expertise with which psychologists wield their tools for achieving laboratory control may have had the unwelcome effect of blinding psychologists to the possibilities of discovering principles of behavior without conducting experiments. When creatively interrogated, a diverse range of large, real-world data sets provides powerful diagnostic tools for revealing principles of human judgment, perception, categorization, decision-making, language use, inference, problem solving, and representation. Examples of these data sets include patterns of website links, dictionaries, logs of group interactions, collections of images and image tags, text corpora, history of financial transactions, trends in twitter tag usage and propagation, patents, consumer product sales, performance in high-stakes sporting events, dialect maps, and scientific citations. The goal of this issue is to present some exemplary case studies of mining naturally existing data sets to reveal important principles and phenomena in cognitive science, and to discuss some of the underlying issues involved with conducting traditional experiments, analyses of naturally occurring data, computational modeling, and the synthesis of all three methods.This article serves as the introduction to a TopiCS topic with the same name.  The rest of the downloadable papers in this Topic are:

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Berger, J. (2016). Does presentation order impact choice after delay? Topics in Cognitive Science.

Christiansen, M. H., & Monaghan, P. (2016). Division of labor in vocabulary structure: Insights from corpus analyses. Topics in Cognitive Science, 8, 670โ€“684. doi: 10.1111/tops.12205.

Griffiths, T. L., Abbott, J. T., & Hsu, A. S. (2016). Exploring human cognition using large image databases. Topics in Cognitive Science, 8, 569โ€“588. doi: 10.1111/tops.12209.

Heit, E., & Nicholson, S. P. (2016). Missing the party: Political categorization and reasoning in the absence of party label cues. Topics in Cognitive Science, 8, 697โ€“714. doi: 10.1111/tops.12206.

Koedinger, K. R., Yudelson, M. V., & Pavlik Jr., P. I. (2016). Testing theories of transfer using error rate learning curves. Topics in Cognitive Science, 8, 589โ€“609. doi: 10.1111/tops.12208.

Moat, H. S., Olivola, C. Y., Chater, N., & Preis, T. (2016). Searching choices: Quantifying decision making processes using search engine data. Topics in Cognitive Science, 8, 685โ€“696. doi: 10.1111/tops.12207.

Pope, D. G. (2016). Exploring psychology in the field: Steps and examples from the used-car market. Topics in Cognitive Science, 8, 660โ€“669. doi: 10.1111/tops.12210.

Vincent-Lamarre, P., Blondin Masse, A., Lopes, M., Lord, M., Marcotte, O., & Harnad, S. (2016). The latent structure of dictionaries. Topics in Cognitive Science, 8, 625โ€“659. doi: 10.1111/tops.12211.


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