| Item type |
学術雑誌論文 / Journal Article(1) |
| 公開日 |
2024-02-28 |
| タイトル |
|
|
タイトル |
Transfer language selection for zero-shot cross-lingual abusive language detection |
|
言語 |
en |
| 言語 |
|
|
言語 |
eng |
| 資源タイプ |
|
|
資源 |
http://purl.org/coar/resource_type/c_6501 |
|
タイプ |
journal article |
| アクセス権 |
|
|
アクセス権 |
open access |
|
アクセス権URI |
http://purl.org/coar/access_right/c_abf2 |
| 著者 |
Juuso Eronen
Michal Ptaszynski
Fumito Masui
Masaki Arata
Gniewosz Leliwa
Michal Wroczynski
|
| 抄録 |
|
|
内容記述タイプ |
Abstract |
|
内容記述 |
We study the selection of transfer languages for automatic abusive language detection. Instead of preparing a dataset for every language, we demonstrate the effectiveness of cross-lingual transfer learning for zero-shot abusive language detection. This way we can use existing data from higher-resource languages to build better detection systems for low-resource languages. Our datasets are from seven different languages from three language families. We measure the distance between the languages using several language similarity measures, especially by quantifying the World Atlas of Language Structures. We show that there is a correlation between linguistic similarity and classifier performance. This discovery allows us to choose an optimal transfer language for zero shot abusive language detection. |
|
言語 |
en |
| 書誌情報 |
en : Information Processing & Management
巻 59,
号 4,
発行日 2022-07
|
| ISSN |
|
|
収録物識別子タイプ |
PISSN |
|
収録物識別子 |
0306-4573 |
| DOI |
|
|
|
識別子タイプ |
DOI |
|
|
関連識別子 |
https://doi.org/10.1016/j.ipm.2022.102981 |
| 権利 |
|
|
言語 |
en |
|
権利情報 |
c2022 Elsevier Ltd. All rights reserved. |
| 出版者 |
|
|
出版者 |
Elsevier |
|
言語 |
en |
| 著者版フラグ |
|
|
言語 |
en |
|
値 |
author |
| 出版タイプ |
|
|
出版タイプ |
AM |
|
出版タイプResource |
http://purl.org/coar/version/c_ab4af688f83e57aa |
2206.00962.pdf (701 KB)
