Citation

Otto AR, Eichstaedt JC. PLoS One 2018; 13(11): e0206923.

Affiliation

Positive Psychology Center, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.

Copyright

(Copyright © 2018, Public Library of Science)

DOI

10.1371/journal.pone.0206923

PMID

30485304

Abstract

Fluctuations in mood states are driven by unpredictable outcomes in daily life but also appear to drive consequential behaviors such as risk-taking. However, our understanding of the relationships between unexpected outcomes, mood, and risk-taking behavior has relied primarily upon constrained and artificial laboratory settings. Here we examine, using naturalistic datasets, how real-world unexpected outcomes predict mood state changes observable at the level of a city, in turn predicting changes in gambling behavior. By analyzing day-to-day mood language extracted from 5.2 million location-specific and public Twitter posts or 'tweets', we examine how real-world 'prediction errors'-local outcomes that deviate positively from expectations-predict day-to-day mood states observable at the level of a city. These mood states in turn predicted increased per-person lottery gambling rates, revealing how interplay between prediction errors, moods, and risky decision-making unfolds in the real world. Our results underscore how social media and naturalistic datasets can uniquely allow us to understand consequential psychological phenomena.

Language: en