The assessment of psychological richness, meaning, and happiness with social media text data: Predictive accuracy and distinct behavioral correlates
Cavan V. Bonner, Young-Min Cho, Fanyi Zhang, Louis Tay, Lyle Ungar, Sharath Chandra Guntuku
TL;DR
This paper explores how well social media text can predict different aspects of well-being, finding that psychological richness is uniquely linked to specific language patterns.
Contribution
The study introduces psychological richness as a new well-being dimension with distinct linguistic predictors compared to hedonic and eudaimonic well-being.
Findings
Language features improved prediction accuracy for psychological richness but not for hedonic or eudaimonic well-being.
Psychological richness had the lowest prediction accuracy (r = .21) compared to other well-being dimensions.
Linguistic features associated with psychological richness showed discriminant validity with unique content and direction.
Abstract
Assessing well-being with social media text data is a promising method, but besides hedonic well-being, little is known about whether additional well-being dimensions, such as psychological richness and eudaimonic well-being, can be predicted from such data. We compare the predictive accuracy for hedonic well-being, eudaimonic well-being, and the recently proposed construct of psychological richness in a large sample of Facebook users (n = 2,644), and find that the inclusion of language features incrementally improved model prediction accuracy beyond demographic features for psychological richness, but not for hedonic or eudaimonic well-being. Psychological richness had the lowest overall prediction accuracy (r = .21) followed by hedonic well-being (r = .27) and eudeomonic well-being (r = .29). The linguistic features associated with Psychological Richness were face valid, and in many…
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Taxonomy
TopicsMental Health via Writing · Impact of Technology on Adolescents · Personality Traits and Psychology