Unraveling multiparty conversations: From human interaction mechanisms to conversational agent challenges and persona design

Multiparty conversations are ubiquitous and indispensable in diverse social and collaborative contexts. However, current conversational agents (CAs) face significant challenges in effectively engaging in such interactions, particularly within text-based environments. While earlier limitations were often attributed to the inadequacies of AI models, recent advances in large language models now compel us to revisit both our understanding of multiparty conversation and the way we design CAs. This paper synthesizes findings from two complementary qualitative investigations and proposes a conceptual model for designing CAs that can genuinely participate, rather than merely function as tools or outsiders. The first study, employing retrospective think-aloud sessions (N=30) with users in text-based multiparty settings, uncovers 5 key interactional mechanisms (e.g., Turn-taking Management, Presence Management) that underpin successful human-human multiparty interactions, derived from participants’ articulated perceptions and reasoning. Subsequently, the second study, through semi-structured interviews (N=15), identifies user expectations for CA integration and key traits (e.g., proactivity, social authenticity) that shape an ideal CA persona perceived by users as a genuine participant. Drawing from these human-centric insights, we then derive design considerations, aiming to guide the development of CAs capable of more natural, effective, and socially intelligent participation in multiparty conversation. • An empirical analysis of 5 key mechanisms that underpin successful human-human text-based multiparty conversations. • An identification of 4 traits that constitute an ideal conversational agent persona for multiparty settings. • A conceptual model synthesizing these mechanisms and persona traits for designing CAs in multiparty participation.

Authors

Institutions

Publication Details

Journal
International Journal of Human-Computer Studies
Published
2025-12-19
DOI
https://doi.org/10.1016/j.ijhcs.2025.103719
Citations
1
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
2.48
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Unraveling multiparty conversations: From human interaction mechanisms to conversational agent challenges and persona design

Shitao Fang, Koji Yatani, Xingyu Liu, Takeo Igarashi
1 citations
International Journal of Human-Computer Studies
AI in Service Interactions
2.48
article

Unraveling multiparty conversations: From human interaction mechanisms to conversational agent challenges and persona design

Shitao Fang, Koji Yatani, Xingyu Liu, Takeo Igarashi
article en
1 citations

Abstract

Multiparty conversations are ubiquitous and indispensable in diverse social and collaborative contexts. However, current conversational agents (CAs) face significant challenges in effectively engaging in such interactions, particularly within text-based environments. While earlier limitations were often attributed to the inadequacies of AI models, recent advances in large language models now compel us to revisit both our understanding of multiparty conversation and the way we design CAs. This paper synthesizes findings from two complementary qualitative investigations and proposes a conceptual model for designing CAs that can genuinely participate, rather than merely function as tools or outsiders. The first study, employing retrospective think-aloud sessions (N=30) with users in text-based multiparty settings, uncovers 5 key interactional mechanisms (e.g., Turn-taking Management, Presence Management) that underpin successful human-human multiparty interactions, derived from participants’ articulated perceptions and reasoning. Subsequently, the second study, through semi-structured interviews (N=15), identifies user expectations for CA integration and key traits (e.g., proactivity, social authenticity) that shape an ideal CA persona perceived by users as a genuine participant. Drawing from these human-centric insights, we then derive design considerations, aiming to guide the development of CAs capable of more natural, effective, and socially intelligent participation in multiparty conversation. • An empirical analysis of 5 key mechanisms that underpin successful human-human text-based multiparty conversations. • An identification of 4 traits that constitute an ideal conversational agent persona for multiparty settings. • A conceptual model synthesizing these mechanisms and persona traits for designing CAs in multiparty participation.

International Journal of Human-Computer StudiesVol. 208
University of California, Los Angeles (US), The University of Tokyo (JP)
Openalex Percentile: Top 8%
AI in Service Interactions
2.48
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.