Title
Are Your Friends Also Haters? Identification of Hater Networks on Social Media: Data Paper
Abstract
ABSTRACT 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.
Year
DOI
Venue
2021
10.1145/3442442.3452310
International World Wide Web Conference
Keywords
DocType
Citations 
hate speech, abusive language, dataset, network analysis, machine learning, classification
Conference
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Maximilian Wich101.69
Melissa Breitinger200.34
Wienke Strathern301.01
Marlena Naimarevic400.34
Georg Groh51079.33
Jürgen Pfeffer611.02