In this paper, we present our approach to the task of identification of persuasion techniques in text, which is a subtask of the SemEval-2023 Task 3 on the multilingual detection of genre, framing, and persuasion techniques in online news. The subtask is multi-label at the paragraph level and the inventory considered by the organizers covers 23 persuasion techniques. Our solution is based on an ensemble of a variety of pre-trained language models (PLMs) fine-tuned on the propaganda dataset. We first describe our system, the different experimental setups we considered, and then provide the results on the dev and test sets released by the organizers. The official evaluation shows our solution ranks 1st in English and attains high scores in all the other languages, i.e. French, German, Italian, Polish, and Russian. We also perform an extensive analysis of the data and the annotations to investigate how they can influence the quality of our systems.
APatt at SemEval-2023 Task 3: The Sapienza NLP System for Ensemble-based Multilingual Propaganda Detection / Purificato, Antonio; Navigli, Roberto. - (2023). (Intervento presentato al convegno 17th International Workshop on Semantic Evaluation, SemEval 2023, co-located with the 61st Annual Meeting of the Association for Computational Linguistics, ACL 2023 tenutosi a Toronto, Canada) [10.18653/v1/2023.semeval-1.51].
APatt at SemEval-2023 Task 3: The Sapienza NLP System for Ensemble-based Multilingual Propaganda Detection
Antonio Purificato
;Roberto Navigli
2023
Abstract
In this paper, we present our approach to the task of identification of persuasion techniques in text, which is a subtask of the SemEval-2023 Task 3 on the multilingual detection of genre, framing, and persuasion techniques in online news. The subtask is multi-label at the paragraph level and the inventory considered by the organizers covers 23 persuasion techniques. Our solution is based on an ensemble of a variety of pre-trained language models (PLMs) fine-tuned on the propaganda dataset. We first describe our system, the different experimental setups we considered, and then provide the results on the dev and test sets released by the organizers. The official evaluation shows our solution ranks 1st in English and attains high scores in all the other languages, i.e. French, German, Italian, Polish, and Russian. We also perform an extensive analysis of the data and the annotations to investigate how they can influence the quality of our systems.File | Dimensione | Formato | |
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