Role-playing games (RPGs) have a considerable amount of text in video game dialogues. Quite often this text is semi-annotated by the game developers. In this paper, we extract a multilingual dataset of persuasive dialogue from several RPGs. We show the viability of this data in building a persuasion detection system using a natural language processing (NLP) model called BERT. We believe that video games have a lot of unused potential as a datasource for a variety of NLP tasks. The code and data described in this paper are available on Zenodo.
Multilingual Persuasion Detection: Video Games as an Invaluable Data Source for NLP
A multilingual dataset of persuasive dialogue from RPGs is used to build a persuasion detection system using BERT, demonstrating the potential of video games as a natural language processing resource.
- Year
- 2022
- Venue
- arXiv 2022
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- 3
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- Abstract onlyARXIV-DEFAULT
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- arxiv.org/abs/2207.04453ARXIV-DEFAULT
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