Online support communities have become vital spaces offering varied forms of support to individuals facing mental health challenges. Despite the proliferation of platforms with distinct technical structures, little is known about how these features shape support dynamics and the socio-technical mechanisms at play. This study introduces a technical-structural-functional model of social support and systematically compares communication network structures and support types in 20 forum-based and 20 chat-based mental health communities. Using supervised machine learning and social network analysis, we find that forum-based communities foster more informational and emotional support, whereas chat-based communities promote greater companionship. These patterns were partially explained by network structure: higher in-degree centralization in forums accounted for the prevalence of informational support, while decentralized reply patterns in chat groups accounted for more companionship. These findings extend the structural-functional model of support to online contexts and provide actionable guidance for designing support communities that align technical structures with users' support needs.

翻译：在线支持社区已成为向面临心理健康挑战的个体提供多样化支持的重要空间。尽管具有不同技术架构的平台不断涌现，但这些技术特性如何影响支持动态及其背后的社会技术机制仍鲜为人知。本研究提出了社会支持的技术-结构-功能模型，并系统比较了20个论坛式与20个聊天式心理健康社区的交流网络结构及支持类型。通过监督机器学习与社会网络分析，我们发现论坛式社区催生了更多信息性与情感性支持，而聊天式社区则促进了更多陪伴性支持。这些模式部分可由网络结构解释：论坛中较高的入度中心化程度解释了信息性支持的普遍性，而聊天群组中分散化的回复模式则对应着更多的陪伴性支持。这些发现将支持的结构-功能模型扩展至在线情境，并为设计符合用户支持需求与技术架构相协调的支持社区提供了可操作的指导。