| アイテムタイプ |
会議発表論文 / Conference Paper(1) |
| 公開日 |
2025-06-04 |
| タイトル |
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タイトル |
Synchronizing Approach in Designing Annotation Guidelines for Multilingual Datasets: A COVID-19 Case Study Using English and Japanese Tweets |
| 言語 |
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言語 |
eng |
| 資源タイプ |
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資源タイプ |
conference paper |
| アクセス権 |
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アクセス権 |
open access |
| 著者 |
Ferawati, Kiki
She, Wan Jou
若宮, 翔子
荒牧, 英治
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| 抄録 |
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内容記述タイプ |
Abstract |
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内容記述 |
The difference in culture between the U.S. and Japan is a popular subject for Western vs. Eastern cultural comparison for researchers. One particular challenge is to obtain and annotate multilingual datasets. In this study, we utilized COVID-19 tweets from the two countries as a case study, focusing particularly on discussions concerning masks. The annotation task was designed to gain insights into societal attitudes toward the mask policies implemented in both countries. The aim of this study is to provide a practical approach for the annotation task by thoroughly documenting how we aligned the multilingual annotation guidelines to obtain a comparable dataset. We proceeded to document the effective practices during our annotation process to synchronize our multilingual guidelines. Furthermore, we discussed difficulties caused by differences in expression style and culture, and potential strategies that helped improve our agreement scores and reduce discrepancies between the annotation results in both languages. These findings offer an alternative method for synchronizing multilingual annotation guidelines and achieving feasible agreement scores for cross-cultural annotation tasks. This study resulted in a multilingual guideline in English and Japanese to annotate topics related to public discourses about COVID-19 masks in the U.S. and Japan. |
| 書誌情報 |
en : Proceedings of the 2nd Workshop on Cross-Cultural Considerations in NLP
p. 32-41,
発行日 2024-08-16
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| 会議情報 |
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会議名 |
In Proceedings of the 2nd Workshop on Cross-Cultural Considerations in NLP (C3NLP 2024) |
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開始年 |
2024 |
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開始月 |
08 |
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開始日 |
11 |
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終了年 |
2024 |
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終了月 |
08 |
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終了日 |
16 |
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開催地 |
Bangkok, Thailand |
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開催国 |
THA |
| 出版者 |
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出版者 |
Association for Computational Linguistics |
| 出版者版DOI |
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関連タイプ |
isReplacedBy |
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識別子タイプ |
DOI |
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関連識別子 |
https://doi.org/10.18653/v1/2024.c3nlp-1.3 |
| 出版者版URI |
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関連タイプ |
isReplacedBy |
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識別子タイプ |
URI |
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関連識別子 |
https://aclanthology.org/2024.c3nlp-1.3/ |
| 権利 |
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権利情報Resource |
https://creativecommons.org/licenses/by/4.0/ |
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権利情報 |
$00A92024 Association for Computational Linguistics |
| 著者版フラグ |
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出版タイプ |
NA |
| 助成情報 |
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助成機関名 |
Japan Science and Technology Agency(JST), SICORP |
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研究課題番号 |
JPMJSC2107 |
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研究課題名 |
プライバシー強化型の移動・社会相互作用分析によるハイパーローカル危機監視とパンデミック対策 |
| 助成情報 |
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助成機関名 |
Japan Society for the Promotion of Science (JSPS) |
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研究課題番号 |
JP22K12041 |
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研究課題名 |
Webビッグデータを用いたパンデミックにおける人々の思いの計量化と可視化 |
