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IReLIIT(BHU) at SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization

Year: 2026

Type: conference-paper

Abstract: This paper presents the IReL_IIT(BHU) submission to SemEval-2026 Task 9 for the Chinese language track.We participated in all three subtasks: binary polarization detection, multi-label polarization type classification, and multi-label manifestation identification.Our approach is based on a unified transformerbased framework with cross-validation, prediction aggregation, and threshold optimization to improve robustness across tasks.On the official evaluation, our systems achieved Macro-F1 scores of 0.9081, 0.7962, and 0.6484 for Subtasks 1, 2, and 3, respectively on test data.

Source: International Workshop on Semantic Evaluation (SemEval)

DOI: 10.18653/v1/2026.semeval-1.297

Authors: Soumadip Majumder, Arjun Mukherjee, Krishna Tewari, Sanjaya Lenka, Sukomal Pal

Institution: Indian Institute of Technology BHU

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W7166842621

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