arXiv:2411.06477

VocalTweets: Investigating Social Media Offensive Language Among Nigerian Musicians

Sunday Oluyele, Juwon Akingbade, Victor Akinode

제출 2024-11-10

원문 초록

Musicians frequently use social media to express their opinions, but they often convey different messages in their music compared to their posts online. Some utilize these platforms to abuse their colleagues, while others use it to show support for political candidates or engage in activism, as seen during the #EndSars protest. There are extensive research done on offensive language detection on social media, the usage of offensive language by musicians has received limited attention. In this study, we introduce VocalTweets, a code-switched and multilingual dataset comprising tweets from 12 prominent Nigerian musicians, labeled with a binary classification method as Normal or Offensive. We trained a model using HuggingFace's base-Twitter-RoBERTa, achieving an F1 score of 74.5. Additionally, we conducted cross-corpus experiments with the OLID dataset to evaluate the generalizability of our dataset.

함께 살펴볼 논문

공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.

arXiv:2506.21002공통 태그 Binary Classification공식 코드 · Papers with Code

Inverse Scene Text Removal

토론

이 논문과 연결된 포럼 글이 아직 없습니다.