Abstract:
As humans, we express sadness, anger, happiness, frustration, bullying, etc., in both physical and virtual
worlds. In the virtual world, i.e., social media, we use textual ways to express ourselves. Due to the
lack of offensive and threatening language detection mechanisms aggressive behavior in social media
is not always followed by an immediate consequence. But the impact of these posts on the victim
can cause prolonged mental illness and instigate fear for social media platforms. This paper aims to
identify threatening posts using deep learning transformer-based models such as Roberta. The Urdu
tweet dataset used in this study has been provided by HASOC-2021 which aims to identify Hate speech
and offensive remarks without human assistance. We submitted our model in its subtask B of the 4th
subtrack(Abusive and Threatening language detection in Urdu), secured 2nd position on the public
leaderboard, and obtained Weighted f1 of 0.5346 and ROC AUC of 0. 8199.