Warning**: this paper contains content that may be offensive or upsetting.* Most hate speech
datasets neglect the cultural diversity within a single language, resulting in a critical …

English datasets predominantly reflect the perspectives of certain nationalities, which can
lead to cultural biases in models and datasets. This is particularly problematic in tasks …

Hate speech is a complex and subjective phenomenon. In this paper, we present a dataset
(GAZE4HATE) that provides gaze data collected in a hate speech annotation experiment …

In this paper, we present a study of efficient data selection and annotation strategies for
Amharic hate speech. We also build various classification models and investigate the …

Social media is a concept developed to link people and make the globe smaller. But it has
recently developed into a center for sexist memes that target especially women. As a result …

Warning: this paper contains content that may be offensive or upsetting Hate speech
moderation on global platforms poses unique challenges due to the multimodal and …

Hate speech detection models are only as good as the data they are trained on. Datasets
sourced from social media suffer from systematic gaps and biases, leading to unreliable …

Social media research is currently confronted with a datasharing problem, as social media
platforms prohibit full data distribution in their terms of service. Until recent changes to the …

The automatic detection of disinformation has gained an increased focus by the research
community during the last years. The spread of false information can be an issue for political …

Despite regulations imposed by nations and social media platforms, such as recent EU
regulations targeting digital violence, abusive content persists as a significant challenge …