Multilingual Persuasion Detection: Video Games as an Invaluable Data Source for NLP

TL;DR

This paper introduces a multilingual dataset of persuasive dialogues from RPGs and demonstrates its usefulness in developing a persuasion detection system using BERT, highlighting video games as a valuable NLP data source.

Contribution

It provides a new multilingual dataset from RPGs and shows its effectiveness for persuasion detection with BERT, emphasizing video games as an untapped NLP resource.

Findings

Successful extraction of persuasive dialogue data from RPGs.

Effective persuasion detection using BERT on the dataset.

Open access to code and data for further research.

Abstract

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.