When a Language Question Is at Stake. A Revisited Approach to Label Sensitive Content

التفاصيل البيبلوغرافية
العنوان: When a Language Question Is at Stake. A Revisited Approach to Label Sensitive Content
المؤلفون: Daria, Stetsenko
سنة النشر: 2023
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Computation and Language
الوصف: Many under-resourced languages require high-quality datasets for specific tasks such as offensive language detection, disinformation, or misinformation identification. However, the intricacies of the content may have a detrimental effect on the annotators. The article aims to revisit an approach of pseudo-labeling sensitive data on the example of Ukrainian tweets covering the Russian-Ukrainian war. Nowadays, this acute topic is in the spotlight of various language manipulations that cause numerous disinformation and profanity on social media platforms. The conducted experiment highlights three main stages of data annotation and underlines the main obstacles during machine annotation. Ultimately, we provide a fundamental statistical analysis of the obtained data, evaluation of models used for pseudo-labelling, and set further guidelines on how the scientists can leverage the corpus to execute more advanced research and extend the existing data samples without annotators' engagement.
Comment: Ukrainian language, pseudo-labelling, dataset, offensive-language
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2311.10514
رقم الانضمام: edsarx.2311.10514
قاعدة البيانات: arXiv