Annotated Slovak Datasets for Toxicity, Hate Speech, and Sentiment Analysis

Abstract

The rise of social media has led to an increase in toxic language, hate speech, and offensive content. While extensive research exists for widely spoken languages like English, Slovak remains underrepresented due to the lack of high-quality datasets. This gap limits the development of effective models for toxicity detection and sentiment analysis in Slovak. To address this, we introduce three new annotated Slovak datasets focused on toxic language, offensive language, hate speech detection, and sentiment analysis. These native datasets provide a more reliable foundation for automated moderation compared to machine-translated alternatives. Our research also highlights the real-world impact of online toxicity, including social polarization and psychological distress, emphasizing the need for proactive detection systems on social media platforms. This paper reviews existing Slovak datasets, presents our newly developed resources, and provides a comparative analysis. Finally, we outline key contributions and suggest future directions for improving toxic language detection in Slovak.