Social media is a potential source of information that infers latent mental
states through Natural Language Processing (NLP). While narrating real-life
experiences, social media users convey their feeling of loneliness or isolated
lifestyle, impacting their mental well-being. Existing literature on
psychological theories points to loneliness as the major consequence of
interpersonal risk factors, propounding the need to investigate loneliness as a
major aspect of mental disturbance. We formulate lonesomeness detection in
social media posts as an explainable binary classification problem, discovering
the users at-risk, suggesting the need of resilience for early control. To the
best of our knowledge, there is no existing explainable dataset, i.e., one with
human-readable, annotated text spans, to facilitate further research and
development in loneliness detection causing mental disturbance. In this work,
three experts: a senior clinical psychologist, a rehabilitation counselor, and
a social NLP researcher define annotation schemes and perplexity guidelines to
mark the presence or absence of lonesomeness, along with the marking of
text-spans in original posts as explanation, in 3,521 Reddit posts. We expect
the public release of our dataset, LonXplain, and traditional classifiers as
baselines via GitHub.

研究探讨了如何利用自然语言处理从社交媒体的信息中推断潜在的心理状态，发现社交媒体用户在讲述日常经历时传达了他们的孤独或孤立的生活方式，对其心理健康产生影响。研究者们将社交媒体帖子中的孤独感检测作为一个可解释的二分类问题，发现了高风险用户，并建议早期采取应对孤独的措施。同时，提出了一个可读性强的数据集 LonXplain，其中包含了 1, 3, 521 Reddit 帖子的人工注释，旨在进一步研究和发展孤独感引起的心理障碍检测技术。

LonXplain: Reddit 帖子中精神障碍所导致的孤独感

LonXplain: Lonesomeness as a Consequence of Mental Disturbance in Reddit  Posts

Loneliness and social isolation are serious and widespread problems among
older people, affecting their physical and mental health, quality of life, and
longevity. In this paper, we propose a ChatGPT-based conversational companion
system for elderly people. The system is designed to provide companionship and
help reduce feelings of loneliness and social isolation. The system was
evaluated with a preliminary study. The results showed that the system was able
to generate responses that were relevant to the created elderly personas.
However, it is essential to acknowledge the limitations of ChatGPT, such as
potential biases and misinformation, and to consider the ethical implications
of using AI-based companionship for the elderly, including privacy concerns.

本文提出了一种 ChatGPT - 基于的会话伴侣系统，旨在为老年人提供陪伴并减少孤独和社交孤立感的情感问题。该系统经过了初步研究的评估，结果表明它能够生成与创建的老年人物质相关的回应。然而，使用基于人工智能的陪伴服务对老年人包括隐私问题在内的伦理问题需要引起注意。

为老年人设计 ChatGPT 对话伴侣

Towards Designing a ChatGPT Conversational Companion for Elderly People

Loneliness has been associated with negative outcomes for physical and mental
health. Understanding how people express and cope with various forms of
loneliness is critical for early screening and targeted interventions to reduce
loneliness, particularly among vulnerable groups such as young adults. To
examine how different forms of loneliness and coping strategies manifest in
loneliness self-disclosure, we built a dataset, FIG-Loneliness (FIne-Grained
Loneliness) by using Reddit posts in two young adult-focused forums and two
loneliness related forums consisting of a diverse age group. We provided
annotations by trained human annotators for binary and fine-grained loneliness
classifications of the posts. Trained on FIG-Loneliness, two BERT-based models
were used to understand loneliness forms and authors' coping strategies in
these forums. Our binary loneliness classification achieved an accuracy above
97%, and fine-grained loneliness category classification reached an average
accuracy of 77% across all labeled categories. With FIG-Loneliness and model
predictions, we found that loneliness expressions in the young adults related
forums were distinct from other forums. Those in young adult-focused forums
were more likely to express concerns pertaining to peer relationship, and were
potentially more sensitive to geographical isolation impacted by the COVID-19
pandemic lockdown. Also, we showed that different forms of loneliness have
differential use in coping strategies.

通过使用 Reddit 帖子，构建了 FIG-Loneliness 数据集，并使用经过培训的人类标注者提供了关于帖子的二元和细粒度孤独分类的注释。使用 FIG-Loneliness 和 BERT-based 模型，我们发现，年轻人所表达的孤独感在一些方面与其他论坛中的表达有所不同，他们更倾向于表达与同龄人关系相关的问题，并因 COVID-19 疫情的影响而更容易受到地理孤立的影响。此外，我们证明了不同形式的孤独在应对策略上的使用有所不同。