Work

ReDASPersuasion at ArAIEval Shared Task: Multilingual and Monolingual Models For Arabic Persuasion Detection

Year: 2023

Type: conference-paper

Abstract: To enhance persuasion detection, we investigate the use of multilingual systems on Arabic data by conducting a total of 22 experiments using baselines, multilingual, and monolingual language transformers.Our aim is to provide a comprehensive evaluation of the various systems employed throughout this task, with the ultimate goal of comparing their performance and identifying the most effective approach.Our empirical analysis shows that ReDASPersuasion system performs best when combined with multilingual "XLM-RoBERTa" and monolingual pre-trained transformers on Arabic dialects like "CAMeLBERT-DA SA" depending on the NLP classification task.

Source: Arabic Natural Language Processing Conference (ArabicNLP)

DOI: 10.18653/v1/2023.arabicnlp-1.54

Authors: Fatima Qachfar, Rakesh Verma

Institution: University of Houston

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: National Science Foundation, Office of Naval Research, Army Research Office