  We present a method for extracting a multilingual sentiment annotated dialog
data set from Fallout New Vegas. The game developers have preannotated every
line of dialog in the game in one of the 8 different sentiments: \textit{anger,
disgust, fear, happy, neutral, pained, sad } and \textit{surprised}. The game
has been translated into English, Spanish, German, French and Italian. We
conduct experiments on multilingual, multilabel sentiment analysis on the
extracted data set using multilingual BERT, XLMRoBERTa and language specific
BERT models. In our experiments, multilingual BERT outperformed XLMRoBERTa for
most of the languages, also language specific models were slightly better than
multilingual BERT for most of the languages. The best overall accuracy was 54\%
and it was achieved by using multilingual BERT on Spanish data. The extracted
data set presents a challenging task for sentiment analysis. We have released
the data, including the testing and training splits, openly on Zenodo. The data
set has been shuffled for copyright reasons.
