The task aims at finding the best techniques to identify and categorize propagandistic tweets from governmental and diplomatic sources on a dataset of tweets in Englsih, posted by authorities of China, Russia, United States and the European Union. The task seeks to classify the tweet into four clusters of propaganda techniques: appeal to commonality, discrediting the opponent, loaded language, appeal to authority.
Publication
Pablo Moral, Guillermo Marco, Julio Gonzalo, Jorge Carrillo-de-Albornoz, Iván Gonzalo-Verdugo (2023) Overview of DIPROMATS 2023: automatic detection and characterization of propaganda techniques in messages from diplomats and authorities of world powers. Procesamiento del Lenguaje Natural, Revista nº 71, septiembre de 2023, pp. 397-407.
Language
English
NLP topic
Abstract task
Dataset
Year
2023
Publication link
Ranking metric
ICM
Task results
| System | F1 |
|---|---|
| ixambert-base-cased | 0.4900 |
| distilbert-base-multilingual-cased | 0.4500 |
| distilbert-base-uncased | 0.4710 |
| bert-base-multilingual-cased | 0.4800 |
| xlm-roberta-base | 0.5430 |
| bert-base-cased | 0.5000 |
| roberta-base | 0.5200 |
| roberta-large | 0.5500 |
| xlm-roberta-large | 0.5200 |
