ComPeer: A Generative Conversational Agent for Proactive Peer Support
Fuente:
arXiv
Guardado en:
| Autores principales: | , , , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866917742044512256 |
|---|---|
| author | Liu, Tianjian Zhao, Hongzheng Liu, Yuheng Wang, Xingbo Peng, Zhenhui |
| author_facet | Liu, Tianjian Zhao, Hongzheng Liu, Yuheng Wang, Xingbo Peng, Zhenhui |
| contents | Conversational Agents (CAs) acting as peer supporters have been widely studied and demonstrated beneficial for people's mental health. However, previous peer support CAs either are user-initiated or follow predefined rules to initiate the conversations, which may discourage users to engage and build relationships with the CAs for long-term benefits. In this paper, we develop ComPeer, a generative CA that can proactively offer adaptive peer support to users. ComPeer leverages large language models to detect and reflect significant events in the dialogue, enabling it to strategically plan the timing and content of proactive care. In addition, ComPeer incorporates peer support strategies, conversation history, and its persona into the generative messages. Our one-week between-subjects study (N=24) demonstrates ComPeer's strength in providing peer support over time and boosting users' engagement compared to a baseline user-initiated CA. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_18064 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | ComPeer: A Generative Conversational Agent for Proactive Peer Support Liu, Tianjian Zhao, Hongzheng Liu, Yuheng Wang, Xingbo Peng, Zhenhui Human-Computer Interaction Conversational Agents (CAs) acting as peer supporters have been widely studied and demonstrated beneficial for people's mental health. However, previous peer support CAs either are user-initiated or follow predefined rules to initiate the conversations, which may discourage users to engage and build relationships with the CAs for long-term benefits. In this paper, we develop ComPeer, a generative CA that can proactively offer adaptive peer support to users. ComPeer leverages large language models to detect and reflect significant events in the dialogue, enabling it to strategically plan the timing and content of proactive care. In addition, ComPeer incorporates peer support strategies, conversation history, and its persona into the generative messages. Our one-week between-subjects study (N=24) demonstrates ComPeer's strength in providing peer support over time and boosting users' engagement compared to a baseline user-initiated CA. |
| title | ComPeer: A Generative Conversational Agent for Proactive Peer Support |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2407.18064 |