SemEval-2026 Task 9: Detecting Online Polarization

Participate in SemEval-2026 Task 9 to detect multilingual online polarization. Develop models to identify and classify polarized content across 20+ languages.

The SemEval-2026 Task 9 is now open for participation, focusing on detecting multilingual, multicultural, and multievent online polarization. This task aims to improve the understanding of polarization in text across various languages, cultures, and events.

Key aspects include:

• Subtask 1: Identifying polarized text.
• Subtask 2: Classifying polarized content into specific types.
• Subtask 3: Determining the manifestation of polarization.

The task involves over 20 languages and provides a platform for developing models to detect polarized content. For more information, visit the Task Page and join the discussion on Discord.

Tags: SemEval-2026, online polarization detection, multilingual polarization, NLP tasks, polarization classification, machine learning