Video Games as a Corpus: Sentiment Analysis using Fallout New Vegas Dialog - Archive ouverte HAL
Communication Dans Un Congrès Année : 2022

Video Games as a Corpus: Sentiment Analysis using Fallout New Vegas Dialog

Résumé

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: anger, disgust, fear, happy, neutral, pained, sad and 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. CCS CONCEPTS • Computing methodologies → Natural language processing; Natural language generation; Neural networks.
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Dates et versions

hal-03772574 , version 1 (08-09-2022)

Identifiants

Citer

Mika Hämäläinen, Khalid Alnajjar, Thierry Poibeau. Video Games as a Corpus: Sentiment Analysis using Fallout New Vegas Dialog. Proceedings of the 17th International Conference on the Foundations of Digital Games (FDG ’22), Sep 2022, Athens, Greece. ⟨10.1145/3555858.3555930⟩. ⟨hal-03772574⟩

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