Compromised Tweet Detection Using Siamese Networks and fastText Representations

Abstract

The aim of this work is to detect compromised users of tweets based on their writing styles. In this paper, we use Siamese Networks to learn a representation of user tweets that allows us to classify them based on a limited amount of ground truth data. We propose the employment of this classification model to identify compromised user accounts of tweets.