Greetings All,
We are delighted to announce SemEval-2026 Task 9: Detecting Multilingual, Multicultural, and Multievent Online Polarization.
Polarization refers to the sharp division of opinions into opposing groups, often accompanied by hostility and exclusion. This shared task aims to advance our understanding of how polarization manifests in text across languages, cultures, and events. Participants will develop systems to detect and interpret polarized content in contexts such as elections, conflicts, protests, and debates.
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Languages
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We provide data in 20+ languages, including: German, Spanish, English, Arabic, Hausa, Urdu, Amharic, Italian, Russian, Myanmar, Chinese, Nepali, Hindi, Telugu, Persian, Turkish, Bangla, Somali, Emakhuwa, Mozambican Portuguese, Igbo, Khmer, Odia, and Punjabi.
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Subtasks
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Subtask 1 (LIVE): Polarization Detection – Identify whether a text exhibits polarization.
Subtask 2: Polarization Type Classification – Classify polarized content into specific types (e.g., political, social, cultural).
Subtask 3: Manifestation Identification – Determine how polarization is expressed (e.g., language cues, tone, argumentative structure).
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Participation
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Website: https://polar-semeval.github.io/
Register & Submit Results (Subtask 1): https://www.codabench.org/competitions/10522/
Discord (community Q&A and discussion): https://discord.com/invite/RF9MzYwKZP
Google Group (official updates & registration): https://groups.google.com/g/polarization-semeval-2026-participants
We warmly invite the community to participate in this exciting shared task and contribute to advancing multilingual and multicultural NLP research.
Best regards,
SemEval-2026 Task 9 Organizers