From Dyads to Groups: Rethinking Emotional Support with Conversational AI

Fuente: arXiv
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Autori principali: Hu, Yuqing, Xue, Wendao, Yu, Yifan, Tan, Yong
Natura: Preprint
Pubblicazione: 2026
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author Hu, Yuqing
Xue, Wendao
Yu, Yifan
Tan, Yong
author_facet Hu, Yuqing
Xue, Wendao
Yu, Yifan
Tan, Yong
contents Advances in artificial intelligence (AI), together with persistent gaps in access to reliable emotional support, have positioned AI as an increasingly prominent source of emotional assistance. However, most AI-based emotional support applications and prior research focus on one-on-one interactions between users and a single AI agent, leaving the potential advantages of alternative support configurations largely unexplored. Drawing on social support and support group theory, this research examines whether AI-based emotional support delivered by a group of AI agents (group AI support) can constitute a more effective support form than single-agent support (single AI support). We propose that group AI support enhances users' perceived support efficacy, that this effect operates by strengthening users' connectedness with the AI system, and that the composition of support types within AI groups further shapes support outcomes. Three experiments provide convergent support for these claims. By identifying when and why group AI emotional support outperforms single AI support, this work advances theoretical understanding of AI-based emotional support and provides actionable guidance for the design of AI support systems.
format Preprint
id arxiv_https___arxiv_org_abs_2603_00797
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle From Dyads to Groups: Rethinking Emotional Support with Conversational AI
Hu, Yuqing
Xue, Wendao
Yu, Yifan
Tan, Yong
Human-Computer Interaction
Advances in artificial intelligence (AI), together with persistent gaps in access to reliable emotional support, have positioned AI as an increasingly prominent source of emotional assistance. However, most AI-based emotional support applications and prior research focus on one-on-one interactions between users and a single AI agent, leaving the potential advantages of alternative support configurations largely unexplored. Drawing on social support and support group theory, this research examines whether AI-based emotional support delivered by a group of AI agents (group AI support) can constitute a more effective support form than single-agent support (single AI support). We propose that group AI support enhances users' perceived support efficacy, that this effect operates by strengthening users' connectedness with the AI system, and that the composition of support types within AI groups further shapes support outcomes. Three experiments provide convergent support for these claims. By identifying when and why group AI emotional support outperforms single AI support, this work advances theoretical understanding of AI-based emotional support and provides actionable guidance for the design of AI support systems.
title From Dyads to Groups: Rethinking Emotional Support with Conversational AI
topic Human-Computer Interaction
url https://arxiv.org/abs/2603.00797