Are Your Friends Also Haters? Identification of Hater Networks on Social Media: Data Paper

Hate speech on social media platforms has become a severe issue in recent years. To cope with it, researchers have developed machine learning-based classification models. Due to the complexity of the problem, the models are far from perfect. A promising approach to improve them is to integrate social network data as additional features in the classification. Unfortunately, there is a lack of datasets containing text and social network data to investigate this phenomenon. Therefore, we develop an approach to identify and collect hater networks on Twitter that uses a pre-Trained classification model to focus on hateful content. The contributions of this article are (1) an approach to identify hater networks and (2) an anonymized German offensive language dataset that comprises social network data. The dataset consists of 4,647,200 labeled tweets and a social graph with 49,353 users and 122,053 edges.