CyberAgressionAdo-v2: Leveraging Pragmatic-Level Information to Decipher Online Hate in French Multiparty Chats
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Abstract
As a part of the release of the CyberAgressionAdo-V2 dataset, this paper introduces a new tagset that includes tags marking pragmatic-level information occurring in cyberbullying situations. The previous version of this dataset, CyberAgressionAdo-V1, consists of aggressive multiparty chats in French annotated using a hierarchical tagset developed to describe bullying narrative events including the participant roles, the presence of hate speech, the type of verbal abuse, among others. In contrast, CyberAgressionAdo-V2 uses a multi-label, fine-grained tagset marking the discursive role of exchanged messages as well as the context in which they occur — for instance, attack (ATK), defend (DFN), counterspeech (CNS), abet/instigate (AIN), gaslight (GSL), etc. This paper provides a comprehensive overview of the annotation tagset and presents statistical insights derived from its application. Additionally, we address the challenges encountered when annotating pragmatic-level information in this context, conducting a thorough analysis of annotator disagreements. The resulting dataset comprises 19 conversations that have been manually annotated and is now available to facilitate further research in the field.