ParsHate: A Benchmark Dataset for Hate and Target Detection in Persian

• URL: http://arxiv.org/abs/2609.16393v1
• Date: Mon, 14 Sep 2026 22:00:54 GMT
• Title: ParsHate: A Benchmark Dataset for Hate and Target Detection in Persian
• Abstract summary: We introduce ParsHate, a manually annotated dataset of 10,000 Persian tweets spanning 2013-2022.<n>The dataset contains 31% hateful content and supports both hate detection and multi-label fine-grained target identification.<n>ParsHate also distinguishes explicit and implicit hate, marks explicit and implicit targets, and provides span-level rationales.
• Score: 14.566415137135614
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We introduce ParsHate, a manually annotated dataset of 10,000 Persian tweets spanning 2013-2022, representing the first decade-long benchmark for hate speech detection in Persian. The dataset contains 31% hateful content and supports both hate detection and multi-label fine-grained target identification across seven structured target categories. ParsHate also distinguishes explicit and implicit hate, marks explicit and implicit targets, and provides span-level rationales. Data collection combines random and score-stratified temporal sampling to reduce keyword-driven bias while preserving natural label distributions. Applying SOTA models for Persian hate-speech detection on ParsHate shows moderate performance (79% F1), especially with samples from earlier years, and low performance with target identification (25.5% macro-F1). This emphasizes the diverse sampling of hate speech in ParsHate and its challenging nature that requires more advanced methods for better performance. Dataset is made publicly available.

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