Garain at SemEval-2020 Task 12: Sequence based Deep Learning for Categorizing Offensive Language in Social Media

SemEval-2020 Task 12 was OffenseEval: Multilingual Offensive Language\nIdentification in Social Media (Zampieri et al., 2020). The task was subdivided\ninto multiple languages and datasets were provided for each one. The task was\nfurther divided into three sub-tasks: offensive language identification,\nautomatic categorization of offense types, and offense target identification. I\nhave participated in the task-C, that is, offense target identification. For\npreparing the proposed system, I have made use of Deep Learning networks like\nLSTMs and frameworks like Keras which combine the bag of words model with\nautomatically generated sequence based features and manually extracted features\nfrom the given dataset. My system on training on 25% of the whole dataset\nachieves macro averaged f1 score of 47.763%.\n