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Searching Choices: Quantifying Decision-Making Processes Using Search Engine Data.

Helen Susannah Moat1, Christopher Y Olivola2, Nick Chater1

  • 1Behavioural Science, Warwick Business School, University of Warwick, Coventry, CV4 7AL, UK.

Topics in Cognitive Science
|June 2, 2016
PubMed
Summary
This summary is machine-generated.

Search engine data can model human decision-making by reflecting prior experience and information gathering. This offers cognitive scientists a new tool to understand how people make choices, valuing lives and future outcomes.

Keywords:
Behavioral scienceComputational social scienceDecision makingGoogleSearch engine dataWikipedia

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Area of Science:

  • Cognitive Science
  • Computational Social Science
  • Psychology

Background:

  • Human decision-making relies on prior experience and gathered information.
  • Understanding these information sources is crucial for cognitive science.

Purpose of the Study:

  • To investigate the utility of search engine data in modeling human decision-making.
  • To explore how search statistics can inform psychological theories and measure information gathering.

Main Methods:

  • Utilizing search engine statistics (e.g., Google) to model the structure of prior experience.
  • Analyzing search query data to measure information gathering and predict decisions.
  • Comparing cross-national information gathering patterns.

Main Results:

  • Search engine data can estimate the statistical structure of prior experience.
  • Search statistics inform theories on valuing human lives and delayed outcomes.
  • Search query data can measure information gathering and predict decisions, showing cross-national differences.

Conclusions:

  • Search engine data is a valuable resource for cognitive scientists.
  • Search data provides novel insights into the human decision-making process.
  • This approach offers a new tool for understanding cognition and behavior.