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Discovering Psychological Principles by Mining Naturally Occurring Data Sets.

Robert L Goldstone1, Gary Lupyan2

  • 1Department of Psychological and Brain Sciences, and Program in Cognitive Science, Indiana University.

Topics in Cognitive Science
|July 13, 2016
PubMed
Summary
This summary is machine-generated.

Analyzing real-world data offers a powerful alternative to traditional experiments for uncovering cognitive science principles. This approach reveals insights into human behavior, perception, and decision-making without controlled laboratory settings.

Keywords:
Big dataDecision-makingLanguageMemoryPerceptionRepresentationResearchStatistics

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Area of Science:

  • Cognitive Science
  • Psychology
  • Data Science

Background:

  • Traditional laboratory experiments in psychology may limit the discovery of behavioral principles.
  • Expertise in experimental control might inadvertently blind researchers to alternative data sources.

Purpose of the Study:

  • To explore the potential of analyzing large, naturally occurring datasets for cognitive science research.
  • To demonstrate how interrogating real-world data can reveal fundamental principles of human cognition.
  • To discuss the interplay between traditional experiments, data mining, and computational modeling.

Main Methods:

  • Mining diverse, large-scale, real-world datasets (e.g., web links, text corpora, social media trends, sales data).
  • Creative interrogation of existing data to identify patterns and principles.
  • Case study analysis of data mining applications in cognitive science.

Main Results:

  • Real-world data sets provide powerful diagnostic tools for understanding human judgment, perception, categorization, decision-making, language, inference, problem-solving, and representation.
  • Examples include insights derived from website links, dictionaries, interaction logs, image tags, financial transactions, and scientific citations.

Conclusions:

  • Analyzing naturally occurring data is a viable and powerful method for discovering cognitive principles.
  • This approach complements traditional experimental methods and computational modeling.
  • Synthesizing these diverse methodologies offers a comprehensive understanding of human cognition.