fabsam @ AMI: A Convolutional Neural Network Approach (short paper)

Abstract

The presence of misogynistic contents is one of the most crucial problems of social networks. In this paper we present our system for misogyny identification on Twitter. Our approach is based on a convolutional neural network that exploits pretrained word embeddings. We also experimented a comparison among different architectures to understand the effectiveness of our method. The paper also described our submissions to both subtasks A and B to Automatic Misogyny Identification competition at Evalita 2020.