Cognitive network science quantifies feelings expressed in suicide
letters and Reddit mental health communities
- URL: http://arxiv.org/abs/2110.15269v2
- Date: Fri, 29 Oct 2021 08:16:13 GMT
- Title: Cognitive network science quantifies feelings expressed in suicide
letters and Reddit mental health communities
- Authors: Simmi Marina Joseph, Salvatore Citraro, Virginia Morini, Giulio
Rossetti, Massimo Stella
- Abstract summary: This study adopts cognitive network science to reconstruct how individuals report their feelings in clinical narratives like suicide notes or mental health posts.
We transform 142 suicide notes and 77,000 Reddit posts from the r/anxiety, r/depression, r/schizophrenia, and r/do-it-your-own (r/DIY) forums into 5 cognitive networks.
We find strong feelings of sadness across all clinical Reddit boards, added to fear r/depression, and replaced by joy/anticipation.
- Score: 0.5144809478361604
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Writing messages is key to expressing feelings. This study adopts cognitive
network science to reconstruct how individuals report their feelings in
clinical narratives like suicide notes or mental health posts. We achieve this
by reconstructing syntactic/semantic associations between conceptsin texts as
co-occurrences enriched with affective data. We transform 142 suicide notes and
77,000 Reddit posts from the r/anxiety, r/depression, r/schizophrenia, and
r/do-it-your-own (r/DIY) forums into 5 cognitive networks, each one expressing
meanings and emotions as reported by authors. These networks reconstruct the
semantic frames surrounding 'feel', enabling a quantification of prominent
associations and emotions focused around feelings. We find strong feelings of
sadness across all clinical Reddit boards, added to fear r/depression, and
replaced by joy/anticipation in r/DIY. Semantic communities and topic modelling
both highlight key narrative topics of 'regret', 'unhealthy lifestyle' and 'low
mental well-being'. Importantly, negative associations and emotions co-existed
with trustful/positive language, focused on 'getting better'. This emotional
polarisation provides quantitative evidence that online clinical boards possess
a complex structure, where users mix both positive and negative outlooks. This
dichotomy is absent in the r/DIY reference board and in suicide notes, where
negative emotional associations about regret and pain persist but are
overwhelmed by positive jargon addressing loved ones. Our quantitative
comparisons provide strong evidence that suicide notes encapsulate different
ways of expressing feelings compared to online Reddit boards, the latter acting
more like personal diaries and relief valve. Our findings provide an
interpretable, quantitative aid for supporting psychological inquiries of human
feelings in digital and clinical settings.
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