Joint Modelling of Emotion and Abusive Language Detection
The rise of online communication platforms has been accompanied by some undesirable effects, such as the proliferation of aggressive and abusive behaviour online. Aiming to tackle this problem, the natural language processing (NLP) community has experimented with a range of techniques for abuse detection. While achieving substantial success, these methods have so far only focused on modelling the linguistic properties of the comments and the online communities of users, disregarding the emotional state of the users and how this might affect their language. The latter is, however, inextricably linked to abusive behaviour. In this paper, we present the first joint model of emotion and abusive language detection, experimenting in a multi-task learning framework that allows one task to inform the other. Our results demonstrate that incorporating affective features leads to significant improvements in abuse detection performance across datasets.
Code (0)
등록된 구현이 없습니다.
Tasks
Abuse DetectionAbusive LanguageMulti-Task LearningSimilar Papers 제목 키워드 기반
Hate Speech and Offensive Language Detection using an Emotion-aware Shared Encoder
The rise of emergence of social media platforms has fundamentally altered how people communicate, and among the results of these developments is an increase in online use of abusive content. Therefore, automatically dete…
Hate Speech DetectionMultilingual and Multimodal Abuse Detection
The presence of abusive content on social media platforms is undesirable as it severely impedes healthy and safe social media interactions. While automatic abuse detection has been widely explored in textual domain, audi…
Abuse DetectionAttending the Emotions to Detect Online Abusive Language
In recent years, abusive behavior has become a serious issue in online social networks. In this paper, we present a new corpus from a semi-anonymous social media platform, which contains the instances of offensive and ne…
Abusive LanguageLongitudinal Abuse and Sentiment Analysis of Hollywood Movie Dialogues using LLMs
Over the past decades, there has been an increasing concern about the prevalence of abusive and violent content in Hollywood movies. This study uses Large Language Models (LLMs) to explore the longitudinal abuse and sent…
Sentiment AnalysisCross-domain and Cross-lingual Abusive Language Detection: A Hybrid Approach with Deep Learning and a Multilingual Lexicon
The development of computational methods to detect abusive language in social media within variable and multilingual contexts has recently gained significant traction. The growing interest is confirmed by the large numbe…
Abusive Language