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.