Literature DB >> 29432182

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

Robert Thorstad1, Phillip Wolff2.   

Abstract

We use big data methods to investigate how decision-making might depend on future sightedness (that is, on how far into the future people's thoughts about the future extend). In study 1, we establish a link between future thinking and decision-making at the population level in showing that US states with citizens having relatively far future sightedness, as reflected in their tweets, take fewer risks than citizens in states having relatively near future sightedness. In study 2, we analyze people's tweets to confirm a connection between future sightedness and decision-making at the individual level in showing that people with long future sightedness are more likely to choose larger future rewards over smaller immediate rewards. In study 3, we show that risk taking decreases with increases in future sightedness as reflected in people's tweets. The ability of future sightedness to predict decisions suggests that future sightedness is a relatively stable cognitive characteristic. This implication was supported in an analysis of tweets by over 38,000 people that showed that future sightedness has both state and trait characteristics (study 4). In study 5, we provide evidence for a potential mechanism by which future sightedness can affect decisions in showing that far future sightedness can make the future seem more connected to the present, as reflected in how people refer to the present, past, and future in their tweets over the course of several minutes. Our studies show how big data methods can be applied to naturalistic data to reveal underlying psychological properties and processes.

Entities:  

Keywords:  big data; decision-making; future thinking

Mesh:

Year:  2018        PMID: 29432182      PMCID: PMC5828570          DOI: 10.1073/pnas.1706589115

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  25 in total

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Journal:  J Exp Psychol Appl       Date:  2002-06

2.  Future time perspective in schizophrenia.

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Journal:  J Abnorm Psychol       Date:  1956-03

3.  A mechanism for reducing delay discounting by altering temporal attention.

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4.  Episodic future thinking reduces reward delay discounting through an enhancement of prefrontal-mediotemporal interactions.

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5.  Shortened time horizons and insensitivity to future consequences in heroin addicts.

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6.  Gaining insights from social media language: Methodologies and challenges.

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7.  Facilitation in recognizing pairs of words: evidence of a dependence between retrieval operations.

Authors:  D E Meyer; R W Schvaneveldt
Journal:  J Exp Psychol       Date:  1971-10

8.  A neural mechanism mediating the impact of episodic prospection on farsighted decisions.

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Journal:  J Neurosci       Date:  2011-05-04       Impact factor: 6.167

9.  The hidden-zero effect: representing a single choice as an extended sequence reduces impulsive choice.

Authors:  Eran Magen; Carol S Dweck; James J Gross
Journal:  Psychol Sci       Date:  2008-07

10.  Evaluating Amazon's Mechanical Turk as a tool for experimental behavioral research.

Authors:  Matthew J C Crump; John V McDonnell; Todd M Gureckis
Journal:  PLoS One       Date:  2013-03-13       Impact factor: 3.240

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  8 in total

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Authors:  Mohamad El Haj; Ahmed A Moustafa
Journal:  Neurol Sci       Date:  2020-07-10       Impact factor: 3.307

2.  Associations of Weight Bias with Disordered Eating Among Latino and White Men.

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3.  Intergenerational transmission of delay discounting: The mediating role of household chaos.

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Journal:  J Adolesc       Date:  2019-03-12

4.  An Interdisciplinary Approach to Understanding the Psychological Impact of Different Grammaticalizations of the Future.

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Journal:  J Cogn       Date:  2020-05-07

5.  Detecting Temporal Cognition in Text: Comparison of Judgements by Self, Expert and Machine.

Authors:  Erin I Walsh; Janie Busby Grant
Journal:  Front Psychol       Date:  2018-10-26

6.  Cross-situation consistency of mobile App users' psychological needs.

Authors:  Zaoyi Sun; Pei Zhang; Zhiwei Ji; Chuansheng Chen; Qun Wan; Xiuying Qian
Journal:  PLoS One       Date:  2019-04-24       Impact factor: 3.240

7.  Distinctiveness and significance of body dissatisfaction and overvaluation among Latinx/Hispanic and White men and women.

Authors:  Janet A Lydecker; Elizabeth W Cotter; Carlos M Grilo
Journal:  Int J Eat Disord       Date:  2020-11-27       Impact factor: 4.861

8.  Real-world unexpected outcomes predict city-level mood states and risk-taking behavior.

Authors:  A Ross Otto; Johannes C Eichstaedt
Journal:  PLoS One       Date:  2018-11-28       Impact factor: 3.240

  8 in total

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