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Cognitive networks detect structural patterns and emotional complexity in suicide notes
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Stella, Massimo, Swanson, Trevor J., Li, Ying, Hills, Thomas Trenholm and Teixeira, Andreia S. (2022) Cognitive networks detect structural patterns and emotional complexity in suicide notes. Frontiers in Psychology, 13 . 917630. doi:10.3389/fpsyg.2022.917630 ISSN 1664-1078.
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Official URL: http://doi.org/10.3389/fpsyg.2022.917630
Abstract
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.
Item Type: | Journal Article | |||||||||
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Subjects: | B Philosophy. Psychology. Religion > BF Psychology Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software |
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Divisions: | Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School | |||||||||
Library of Congress Subject Headings (LCSH): | Psycholinguistics , Language and emotions , Text data mining , Emotions , Cognitive science | |||||||||
Journal or Publication Title: | Frontiers in Psychology | |||||||||
Publisher: | Frontiers Research Foundation | |||||||||
ISSN: | 1664-1078 | |||||||||
Official Date: | 8 December 2022 | |||||||||
Dates: |
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Volume: | 13 | |||||||||
Article Number: | 917630 | |||||||||
DOI: | 10.3389/fpsyg.2022.917630 | |||||||||
Status: | Peer Reviewed | |||||||||
Publication Status: | Published | |||||||||
Access rights to Published version: | Open Access (Creative Commons) | |||||||||
Date of first compliant deposit: | 1 March 2023 | |||||||||
Date of first compliant Open Access: | 2 March 2023 | |||||||||
RIOXX Funder/Project Grant: |
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