ID | 118262 |
著者 |
Quan, Changqin
Kobe University
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キーワード | Suicide risk prediction
accumulated emotional traits
emotion accumulation
emotion covariance
emotion transition
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資料タイプ |
学術雑誌論文
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抄録 | Suicide has been a major cause of death throughout the world. Recent studies have proved a reliable connection between the emotional traits and suicide. However, detection and prevention of suicide are mostly carried out in the clinical centers, which limits the effective treatments to a restricted group of people. To assist detecting suicide risks among the public, we propose a novel method by exploring the accumulated emotional information from people’s daily writings (i.e. Blogs), and examining these emotional traits which are predictive of suicidal behaviors. A complex emotion topic (CET) model is employed to detect the underlying emotions and emotion-related topics in the Blog streams, based on eight basic emotion categories and five levels of emotion intensities. Since suicide is caused through an accumulative process, we propose three accumulative emotional traits, i.e., accumulation, covariance, and transition of the consecutive Blog emotions, and employ a generalized linear regression algorithm to examine the relationship between emotional traits and suicide risk. Our experiment results suggest that the emotion transition trait turns to be more discriminative of the suicide risk, and that the combination of three traits in linear regression would generate even more discriminative predictions. A classification of the suicide and non-suicide Blog articles in our additional experiment verifies this result. Finally, we conduct a case study of the most commonly mentioned emotion-related topics in the suicidal Blogs, to further understand the association between emotions and thoughts for these authors.
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掲載誌名 |
IEEE Journal of Biomedical and Health Informatics
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ISSN | 21682194
21682208
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cat書誌ID | AA12720964
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出版者 | IEEE
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巻 | 20
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号 | 5
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開始ページ | 1384
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終了ページ | 1396
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発行日 | 2015-07-22
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権利情報 | © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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言語 |
eng
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著者版フラグ |
著者版
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部局 |
理工学系
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