  This study presents for the first time the SWB-J index, a subjective
well-being indicator for Japan based on Twitter data. The index is composed by
eight dimensions of subjective well-being and is estimated relying on Twitter
data by using human supervised sentiment analysis. The index is then compared
with the analogous SWB-I index for Italy, in order to verify possible analogies
and cultural differences. Further, through structural equation models, a causal
assumption is tested to see whether the economic and health conditions of the
country influence the well-being latent variable and how this latent dimension
affects the SWB-J and SWB-I indicators. It turns out that, as expected, the
economic and health welfare is only one aspect of the multidimensional
well-being that is captured by the Twitter-based indicator.
