ReDASPersuasion at SemEval-2023 Task 3: Persuasion Detection using Multilingual Transformers and Language Agnostic Features

Abstract

This paper describes a multilingual persuasion detection system that incorporates persuasion technique attributes for a multi-label classification task. The proposed method has two advantages. First, it combines persuasion features with a sequence classification transformer to classify persuasion techniques. Second, it is a language agnostic approach that supports a total of 100 languages, guaranteed by the multilingual transformer module and the Google translator interface. Our persuasion system outperforms the SemEval baseline in all languages, except zero shot prediction languages, which was not the main focus of our research. With the highest F1-Micro score of 0.45 for Italian, it achieved the eighth position on the leaderboard.