Abstract: We analyze homotransphobic content on Twitter across seven different languages, highlighting how this pervasive issue manifests in distinct cultural contexts worldwide. By developing a comprehensive taxonomy to classify homotransphobic speech, our study establishes a crucial foundation for building effective models to identify and counter such harmful speech on online platforms.