ORIGINAL RESEARCH article
Front. Public Health
Sec. Public Mental Health
This article is part of the Research TopicInnovative Approaches in Psychosocial and Mental HealthView all 21 articles
Exploring Meaning in Life from Social Network Content in the Sleep Scenario
Provisionally accepted
- 1Beijing Normal University, Beijing, China
- 2Wuhan University, Wuhan, China
- 3University of Oxford, Oxford, United Kingdom
- 4Beijing Jiaotong University, Beijing, China
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The exploration of life’s meaning has been a key topic across disciplines, and artificial intelligence is now beginning to investigate it. We leveraged social media to assess meaning in life (MIL) and its associated factors at individual and group levels. We compiled a diverse dataset consisting of microblog posts (N = 7,588,597) and responses from user surveys (N = 448), annotated using a combination of self-assessment, expert opinions, and ChatGPT-generated insights. Our methodology examined MIL in three ways: (1) developing deep learning models to assess MIL components, (2) applying semantic dependency graph algorithms to identify MIL associated factors, and (3) constructing eight subnetworks to analyze factors, their interrelations, and MIL differences. We validated these methods and bridged two foundational MIL theories, highlighting their interconnections. By identifying psychological risk factors, our work may provide clues to mental health issues and inform possible intervention.
Keywords: meaning in life, Social network, factor extraction, semantic analysis, deep learning
Received: 06 Jun 2025; Accepted: 28 Oct 2025.
Copyright: © 2025 Li, Wang, Yan, Jiake, Zhao, Wang, Yao and Cao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Lei Cao, caolei@bnu.edu.cn
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