Work

PolarizedTeam at SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization

Year: 2026

Type: conference-paper

Abstract: This paper presents the systems developed for SemEval-2026 Task 9, which targets the detection and categorization of multilingual, multicultural, and multi-event online polarization across 22 languages.To address the challenges posed by linguistic diversity and short, heterogeneous texts, we evaluate several Transformerbased architectures for multilingual polarization detection.Our approach models the task as a multi-label classification problem and incorporates mean pooling for sentence representation, focal loss to mitigate severe label imbalance, and label-wise attention mechanisms to capture polarization-specific linguistic cues.Experimental results show that combining robust multilingual encoders with label-aware modelling substantially improves the detection of polarized content across diverse communities and events 1 .

Source: International Workshop on Semantic Evaluation (SemEval)

DOI: 10.18653/v1/2026.semeval-1.180

Authors: Maria Nestor, Maroan Al Shrafat, Ioana Pește, Daniela Gifu, Diana Trandabăț

Institutions: Academia Oamenilor de Știință din România, Academia Română, Filiala Iași, Romanian Academy, Alexandru Ioan Cuza University

Language: English

Topic: Hate Speech and Cyberbullying Detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funder: Academia Oamenilor de Știință din România

OpenAlex ID: W7166885275