We investigate whether psychological well-being translates across English and Spanish Twitter, by building and comparing source language and automatically translated weighted lexica in English and Spanish. We find that the source language models perform substantially better than the machine translated versions. Moreover, manually correcting translation errors does not improve model performance, suggesting that meaningful cultural information is being lost in translation. Further work is needed to clarify when automatic translation of well-being lexica is effective and how it can be improved for cross-cultural analysis.