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