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Predicting future mental illness from social media: A big-data approach.

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A big data analysis of the relationship between future thinking and decision-making.

Robert Thorstad1, Phillip Wolff2

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People who think further into the future take fewer risks and prefer larger future rewards. This future sightedness is a stable cognitive trait influencing decision-making.

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big datadecision-makingfuture thinking

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Area of Science:

  • Cognitive Psychology
  • Behavioral Economics
  • Computational Social Science

Background:

  • Decision-making is influenced by cognitive factors.
  • Understanding future-oriented thinking is crucial for predicting behavior.
  • Big data offers novel methods to study psychological traits.

Purpose of the Study:

  • To investigate the relationship between future sightedness and decision-making.
  • To explore future sightedness as a stable cognitive characteristic.
  • To identify mechanisms linking future sightedness to choices.

Main Methods:

  • Analysis of large-scale public data (tweets).
  • Big data analytics to quantify future sightedness.
  • Cross-sectional and longitudinal analyses of individual and population-level data.

Main Results:

  • Greater future sightedness correlates with reduced risk-taking at both state and individual levels.
  • Individuals with longer future sightedness prefer larger future rewards over immediate ones.
  • Future sightedness demonstrates both state and trait characteristics, indicating stability.

Conclusions:

  • Future sightedness is a significant predictor of decision-making.
  • Big data methods can reveal psychological properties from naturalistic data.
  • Future sightedness may influence decisions by enhancing present-future connection.