POLAR: Detecting Multilingual, Multicultural and Multievent Online Polarization
@ SemEval-2026 Task 9
Task Introduction
POLAR @ SemEval-2026 introduces the first shared task dedicated to detecting and analyzing online polarization across multilingual, multicultural, and multievent social media discourse.
- Goal: identify polarized content that reflects sharp divisions or hostility between social, political, religious, ethnic, gender-based, or other identity groups.
- Subtasks: participants may compete in Polarization Detection, Polarization Type Classification, and Polarization Manifestation Identification.
- Data: the task uses posts from news websites, Reddit, blogs, Bluesky, and regional forums, covering events such as elections, conflicts, gender rights, migration, and other public debates.
- Evaluation: all subtasks are evaluated using Macro F1 to encourage robust performance across languages and cultural contexts.
For more details about the exact subtasks definitions, refer to the Subtasks Page.
Languages Covered
The task covers the following 22 languages:
Amharic,
Arabic,
Bengali,
Burmese,
Chinese,
English,
German,
Hausa,
Hindi,
Italian,
Khmer,
Nepali,
Odia,
Persian,
Polish,
Punjabi,
Russian,
Spanish,
Swahili,
Telugu,
Turkish,
Urdu.