Overview of EmoThreat: Emotions and Threat Detection in Urdu at FIRE 2022

Emotion and targeted abuse detection i.e threat, are problems that have been studied in many rich resource languages. However, when it comes to low-resource languages such as Urdu, we find a dearth of resources and methodologies. Our paper presents the findings of the shared task "EmoThreat: Emotions and Threat detection in Urdu", where we focused on presenting resources for multi-label emotion classification (Task A) and binary threat detection (Task B) in Urdu. Task B was further divided into group and individual threat detection, making it a multi-class problem. The paper presents a summary of the methodologies and findings of the ten different participating teams. Each team also presented a thorough error analysis for the best model. The best performing system in Task A achieved a macroF1 score of 0.687, whereas, Task B subtask 1 and subtask 2 achieved 0.716 and 0.539 macro-F1 scores respectively.