Social Support Detection
Shared Task at IberLEF 2026
Competition (data and evaluation) available at Codabench
Competition (data and evaluation) available at Codabench
Title: SSD-2026: Social Support Detection in Social Media
Goal: Build and evaluate NLP systems that (i) detect social support in social-media comments and (ii) identify the target of that support (individual vs. community and the specific community).
Motivation: Move beyond sentiment analysis toward actionable prosocial language understanding, enabling realistic end‑to‑end evaluation for deployment scenarios.
Input: A single social-media comment
Output: Support / Not Support
Definition: The comment expresses encouragement, care, admiration, help, or solidarity toward someone.
Input: Supportive comments
Output: Individual / Group
Definition: Determine whether the support is aimed at a specific person or a collective entity.
Input: Supportive comments targeting a group
Output classes: Nation, Other, LGBTQ, Black Community, Religion, Women
Definition: Identify which community is being supported.
Scope constraint: Supportive comments that explicitly promote violence or harm are labeled as Not Support.