Well-Being Depends on Social Comparison: Hierarchical Models of Twitter Language Suggest That Richer Neighbors Make You Less Happy

Abstract

Psychological research has shown that subjective well-being is sensitive to social comparison effects; individuals report decreased happiness when their neighbors earn more than they do. In this work, we use Twitter language to estimate the well-being of users, and model both individual and neighborhood income using hierarchical modeling across counties in the United States (US). We show that language-based estimates from a sample of 5.8 million Twitter users replicate results obtained from large-scale well-being surveys - relatively richer neighbors leads to lower well-being, even when controlling for absolute income. Furthermore, predicting individual-level happiness using hierarchical models (i.e., individuals within their communities) out-predicts standard baselines. We also explore language associated with relative income differences and find that individuals with lower income than their community tend to swear (f*ck, sh*t, b*tch), express anger (pissed, bullsh*t, wtf), hesitation (don't, anymore, idk, confused) and acts of social deviance (weed, blunt, drunk). These results suggest that social comparison robustly affects reported well-being, and that Twitter language analyses can be used to both measure these effects and shed light on their underlying psychological dynamics.

Figure 1:

Predicting individual happiness with 10 fold cross validation, using flat and hierarchical models (reported Pearson r). Each model includes individual income, age, gender, and education as well as community level income and education. * significant differences between models (p < .001).

Figure 2:

Topics predicted by a negative individual income coefficient and a positive community income coefficient.