Publications

@inproceedings{janez-martino_unileon-unibo_2023,

title = {UniLeon-UniBO at IberLEF 2023 Task DIPROMATS: RoBERTa-based Models to Climb Up the Propaganda Tree in English and Spanish.},

author = {Francisco Jáñez-Martino and Alberto Barrón-Cedeño},

url = {https://ceur-ws.org/Vol-3496/dipromats-paper3.pdf},

year  = {2023},

date = {2023-01-01},

booktitle = {IberLEF@ SEPLN},

abstract = {In this paper, we describe our participation in the IberLEF 2023 shared task DIPROMATS, which focuses on the automatic detection of propaganda in tweets posted by diplomats in English and Spanish. Task 1 involves detecting propaganda (binary classification), while Task 2 and Task 3 categorize the type of propaganda into four groups and 15 techniques (multi-label classification). We propose a pipeline using four multi-label models to identify propaganda techniques, followed by group identification and binary classification. Our submission based on RoBERTa for the English tasks achieved top positions, with scores of 0.1835 for Task 1 (3rd place), 0.1342 for Task 2 (2nd place), and 0.0693 for Task 3 (5th place). For the Spanish tasks, using BERTIN, we achieved 0.6301 for Task 1 (4th place), -0.0134 for Task 2 (1st place), and -0.1478 for Task 3 (1st place).},

keywords = {Diplomats Bias, Multilabel Propaganda Identification, Persuasion Techniques Identification, Twitter},

pubstate = {published},

tppubtype = {inproceedings}

}