POLAR_SemEval_2026

Task 9: Detecting Multilingual, Multicultural And Multievent Online Polarization

Link: https://polar-semeval.github.io/

Introduction

Polarization is the sharp division of opinions into opposing groups, often with hostility and exclusion. This shared task seeks to advance understanding of how polarization appears in text across languages, cultures, and events. Participants will develop models to detect and interpret polarized content from contexts like elections, conflicts, protests, and debates.

In this study, polarization refers to the process or phenomenon in which opinions, beliefs, or behaviors become more extreme or divided, leading to a greater distance or conflict between differing groups. Attitude polarization is the negative attitude that individuals or groups display towards individuals and groups outside their group while also showing blind support and solidarity towards people within their group.

Polarization denotes stereotyping, vilification, dehumanization, deindividuation, or intolerance of other people’s views, beliefs, and identities. In this study, speeches and articles that are shared on social media that incite division, groupism, hatred, conflict, and intolerance are classified as containing polarization.

This task is on polarized opinions and focuses on:

• Assessing whether social media messages reflect attitude polarization and to categorize the various types and manifestations of this polarization.

Task

The task is to detect polarized content from contexts like elections, conflicts, protests, and debates. Link:

1. Polarization Detection: https://www.codabench.org/competitions/10522/
2. Polarization Type Classification: https://www.codabench.org/competitions/10669/
3. Manifestation Identification: https://www.codabench.org/competitions/10674/#/pages-tab

Results

Subtask 1

Subtask 2

Subtask 3