| アイテムタイプ |
会議発表論文 / Conference Paper(1) |
| 公開日 |
2025-06-17 |
| タイトル |
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タイトル |
Loneliness Episodes: A Japanese Dataset for Loneliness Detection and Analysis |
| 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 |
Fujikawa, Naoya
Nguyen, Quang Toan
Ito, Kazuhiro
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 |
|
内容記述 |
Loneliness, a significant public health concern, is closely connected to both physical and mental well-being. Hence, detection and intervention for individuals experiencing loneliness are crucial. Identifying loneliness in text is straightforward when it is explicitly stated but challenging when it is implicit. Detecting implicit loneliness requires a manually annotated dataset because whereas explicit loneliness can be detected using keywords, implicit loneliness cannot be. However, there are no freely available datasets with clear annotation guidelines for implicit loneliness. In this study, we construct a freely accessible Japanese loneliness dataset with annotation guidelines grounded in the psychological definition of loneliness. This dataset covers loneliness intensity and the contributing factors of loneliness. We train two models to classify whether loneliness is expressed and the intensity of loneliness. The model classifying loneliness versus non-loneliness achieves an F1-score of 0.833, but the model for identifying the intensity of loneliness has a low F1-score of 0.400, which is likely due to label imbalance and a shortage of a certain label in the dataset. We validate performance in another domain, specifically X (formerly Twitter), and observe a decrease. In addition, we propose improvement suggestions for domain adaptation. |
| 書誌情報 |
en : Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis
p. 280-293,
発行日 2024-08-15
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| 会議情報 |
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会議名 |
14th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis |
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開始年 |
2024 |
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開始月 |
08 |
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開始日 |
15 |
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終了年 |
2024 |
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終了月 |
08 |
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終了日 |
15 |
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開催期間 |
2024-08-15 - 2024-08-15 |
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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.wassa-1.23 |
| 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.wassa-1.23/ |
| 権利 |
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権利情報Resource |
https://creativecommons.org/licenses/by/4.0/ |
|
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) |
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研究課題番号 |
JPMJMI21J2 |
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研究課題名 |
個人の最適化を支える「場の状態」：個と場の共創的Well-Beingへ |
