A Corpus for Sentence-level Subjectivity Detection on English News Articles
Abstrak
We develop novel annotation guidelines for sentence-level subjectivity detection, which are not limited to language-specific cues. We use our guidelines to collect NewsSD-ENG, a corpus of 638 objective and 411 subjective sentences extracted from English news articles on controversial topics. Our corpus paves the way for subjectivity detection in English and across other languages without relying on language-specific tools, such as lexicons or machine translation. We evaluate state-of-the-art multilingual transformer-based models on the task in mono-, multi-, and cross-language settings. For this purpose, we re-annotate an existing Italian corpus. We observe that models trained in the multilingual setting achieve the best performance on the task.
Topik & Kata Kunci
Penulis (8)
Francesco Antici
Andrea Galassi
Federico Ruggeri
Katerina Korre
Arianna Muti
Alessandra Bardi
Alice Fedotova
Alberto Barrón-Cedeño
Akses Cepat
- Tahun Terbit
- 2023
- Bahasa
- en
- Sumber Database
- arXiv
- Akses
- Open Access ✓