Estimating Relationships between Participants in Multi-Party Chat Corpus

Akane Fukushige, Koji Inoue, Keiko Ochi, Tatsuya Kawahara, Sanae Yamashita, Ryuichiro Higashinaka


Abstract
While most existing dialogue studies focus on dyadic (one-on-one) interactions, research on multi-party dialogues has gained increasing importance. One key challenge in multi-party dialogues is identifying and interpreting the relationships between participants. This study focuses on multi-party chat corpus and aims to estimate participant pairs with specific relationships, such as family and acquaintances. We evaluated the performance of large language models (LLMs) in estimating these relationships, comparing them with a logistic regression model that uses interpretable textual features, including the number of turns and the frequency of honorific expressions. The results show that even advanced LLMs struggle with social relationship estimation, performing worse than a simple heuristic-based approach. This finding highlights the need for further improvement in enabling LLMs to naturally capture social relationships in multi-party dialogues.
Anthology ID:
2026.iwsds-1.38
Volume:
Proceedings of the 16th International Workshop on Spoken Dialogue System Technology
Month:
February
Year:
2026
Address:
Trento, Italy
Editors:
Giuseppe Riccardi, Seyed Mahed Mousavi, Maria Ines Torres, Koichiro Yoshino, Zoraida Callejas, Shammur Absar Chowdhury, Yun-Nung Chen, Frederic Bechet, Joakim Gustafson, Géraldine Damnati, Alex Papangelis, Luis Fernando D’Haro, John Mendonça, Raffaella Bernardi, Dilek Hakkani-Tur, Giuseppe "Pino" Di Fabbrizio, Tatsuya Kawahara, Firoj Alam, Gokhan Tur, Michael Johnston
Venue:
IWSDS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
379–390
Language:
URL:
https://aclanthology.org/2026.iwsds-1.38/
DOI:
Bibkey:
Cite (ACL):
Akane Fukushige, Koji Inoue, Keiko Ochi, Tatsuya Kawahara, Sanae Yamashita, and Ryuichiro Higashinaka. 2026. Estimating Relationships between Participants in Multi-Party Chat Corpus. In Proceedings of the 16th International Workshop on Spoken Dialogue System Technology, pages 379–390, Trento, Italy. Association for Computational Linguistics.
Cite (Informal):
Estimating Relationships between Participants in Multi-Party Chat Corpus (Fukushige et al., IWSDS 2026)
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PDF:
https://aclanthology.org/2026.iwsds-1.38.pdf