multilingual

Respectful or Toxic? Using Zero-Shot Learning with Language Models to Detect Hate Speech

Hate speech detection faces two significant challenges: 1) the limited availability of labeled data and 2) the high variability of hate speech across different contexts and languages. Prompting brings a ray of hope to these challenges. It allows …

The State of Profanity Obfuscation in Natural Language Processing Scientific Publications

Work on hate speech has made considering rude and harmful examples in scientific publications inevitable. This situation raises various problems, such as whether or not to obscure profanities. While science must accurately disclose what it does, the …

A Cross-Lingual Study of Homotransphobia on Twitter

We present a cross-lingual study of homotransphobia on Twitter, examining the prevalence and forms of homotransphobic content in tweets related to LGBT issues in seven languages. Our findings reveal that homotransphobia is a global problem that takes …

Measuring Harmful Representations in Scandinavian Language Models

Scandinavian countries are perceived as role-models when it comes to gender equality. With the advent of pre-trained language models and their widespread usage, we investigate to what extent gender-based harmful and toxic content exist in selected …

Data-Efficient Strategies for Expanding Hate Speech Detection into Under-Resourced Languages

Hate speech is a global phenomenon, but most hate speech datasets so far focus on English-language content. This hinders the development of more effective hate speech detection models in hundreds of languages spoken by billions across the world. More …

The State of Profanity Obfuscation in Natural Language Processing Scientific Publications

Work on hate speech has made the consideration of rude and harmful examples in scientific publications inevitable. This raises various problems, such as whether or not to obscure profanities. While science must accurately disclose what it does, the …

XLM-EMO: Multilingual Emotion Prediction in Social Media Text

Detecting emotion in text allows social and computational scientists to study how people behave and react to online events. However, developing these tools for different languages requires data that is not always available. This paper collects the …