Paper Type
ERF
Abstract
Online cancer communities provide critical emotional support for patients. Within these communities, certain members emerge as emotional opinion leaders whose participation may affect patients’ emotional trajectories. However, it remains unclear whether their influence changes as generative AI tools become more accessible in online communication environments. This study examines emotional opinion leaders in an online breast cancer community before and after the availability of generative AI. Using a large-scale pre-GenAI dataset of 57,154 threads and 226,937 replies, we construct weighted bipartite networks to identify three types of leaders based on participation frequency, content length, and contribution quality. We evaluate their effects on changes in patients’ hope, joy, fear, and sadness. By comparing patterns across periods, this research advances the understanding of how evolving generative AI technologies may influence emotional support and patient well-being in online cancer communities.
Paper Number
1636
Recommended Citation
Xu, Anqi and Gao, Yuanyuan, "Emotional Opinion Leaders in Online Cancer Communities Before and After Generative AI" (2026). AMCIS 2026 Proceedings. 11.
https://aisel.aisnet.org/amcis2026/sig_health/sig_health/11
Emotional Opinion Leaders in Online Cancer Communities Before and After Generative AI
Online cancer communities provide critical emotional support for patients. Within these communities, certain members emerge as emotional opinion leaders whose participation may affect patients’ emotional trajectories. However, it remains unclear whether their influence changes as generative AI tools become more accessible in online communication environments. This study examines emotional opinion leaders in an online breast cancer community before and after the availability of generative AI. Using a large-scale pre-GenAI dataset of 57,154 threads and 226,937 replies, we construct weighted bipartite networks to identify three types of leaders based on participation frequency, content length, and contribution quality. We evaluate their effects on changes in patients’ hope, joy, fear, and sadness. By comparing patterns across periods, this research advances the understanding of how evolving generative AI technologies may influence emotional support and patient well-being in online cancer communities.
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