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Cognitive networks detect structural patterns and emotional complexity in suicide notes
Stella, Massimo1; Swanson, Trevor J. J.2; Li, Ying3,4; Hills, Thomas T. T.5; Teixeira, Andreia S. S.6,7
第一作者Massimo Stella
通讯作者邮箱m.stella@exeter.ac.uk (massimo stella ) ; li@mpib-berlin.mpg.de (ying li )
摘要

Communicating one's mindset means transmitting complex relationships between concepts and emotions. Using network science and word co-occurrences, we reconstruct conceptual associations as communicated in 139 genuine suicide notes, i.e., notes left by individuals who took their lives. We find that, despite their negative context, suicide notes are surprisingly positively valenced. Through emotional profiling, their ending statements are found to be markedly more emotional than their main body: The ending sentences in suicide notes elicit deeper fear/sadness but also stronger joy/trust and anticipation than the main body. Furthermore, by using data from the Emotional Recall Task, we model emotional transitions within these notes as co-occurrence networks and compare their structure against emotional recalls from mentally healthy individuals. Supported by psychological literature, we introduce emotional complexity as an affective analog of structural balance theory, measuring how elementary cycles (closed triads) of emotion co-occurrences mix positive, negative and neutral states in narratives and recollections. At the group level, authors of suicide narratives display a higher complexity than healthy individuals, i.e., lower levels of coherently valenced emotional states in triads. An entropy measure identified a similar tendency for suicide notes to shift more frequently between contrasting emotional states. Both the groups of authors of suicide notes and healthy individuals exhibit less complexity than random expectation. Our results demonstrate that suicide notes possess highly structured and contrastive narratives of emotions, more complex than expected by null models and healthy populations.

关键词data science psycholinguistics complex networks text analysis emotional profiling cognitive network science
2022-12-08
语种英语
DOI10.3389/fpsyg.2022.917630
发表期刊FRONTIERS IN PSYCHOLOGY
ISSN1664-1078
卷号13页码:16
期刊论文类型实证研究
收录类别SSCI
资助项目FCT ; LASIGE Research Unit[UIDB/00408/2020] ; LASIGE Research Unit[UIDP/00408/2020]
出版者FRONTIERS MEDIA SA
WOS关键词PSYCHOLOGICAL PAIN ; PERSONALITY ; IDEATION ; VARIABILITY ; EXPERIENCE ; MIND
WOS研究方向Psychology
WOS类目Psychology, Multidisciplinary
WOS记录号WOS:000902059200001
WOS分区Q1
资助机构FCT ; LASIGE Research Unit
引用统计
被引频次:2[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.psych.ac.cn/handle/311026/44365
专题认知与发展心理学研究室
通讯作者Stella, Massimo; Li, Ying
作者单位1.Univ Exeter, Dept Comp Sci, CogNosco Lab, Exeter, England
2.Univ Kansas, Dept Psychol, Lawrence, KS USA
3.Max Planck Inst Human Dev, Berlin, Germany
4.Chinese Acad Sci, Inst Psychol, Beijing, Peoples R China
5.Univ Warwick, Dept Psychol, Coventry, England
6.Univ Lisbon, Fac Ciencias, Dept Informat, LASIGE, Lisbon, Portugal
7.INESC ID, Lisbon, Portugal
通讯作者单位中国科学院心理研究所
推荐引用方式
GB/T 7714
Stella, Massimo,Swanson, Trevor J. J.,Li, Ying,et al. Cognitive networks detect structural patterns and emotional complexity in suicide notes[J]. FRONTIERS IN PSYCHOLOGY,2022,13:16.
APA Stella, Massimo,Swanson, Trevor J. J.,Li, Ying,Hills, Thomas T. T.,&Teixeira, Andreia S. S..(2022).Cognitive networks detect structural patterns and emotional complexity in suicide notes.FRONTIERS IN PSYCHOLOGY,13,16.
MLA Stella, Massimo,et al."Cognitive networks detect structural patterns and emotional complexity in suicide notes".FRONTIERS IN PSYCHOLOGY 13(2022):16.
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