@inproceedings{bangalore-kantharaju-etal-2020-multimodal,
title = "Multimodal Analysis of Cohesion in Multi-party Interactions",
author = "Bangalore Kantharaju, Reshmashree and
Langlet, Caroline and
Barange, Mukesh and
Clavel, Chlo{\'e} and
Pelachaud, Catherine",
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.lrec-1.63",
pages = "498--507",
abstract = "Group cohesion is an emergent phenomenon that describes the tendency of the group members{'} shared commitment to group tasks and the interpersonal attraction among them. This paper presents a multimodal analysis of group cohesion using a corpus of multi-party interactions. We utilize 16 two-minute segments annotated with cohesion from the AMI corpus. We define three layers of modalities: non-verbal social cues, dialogue acts and interruptions. The initial analysis is performed at the individual level and later, we combine the different modalities to observe their impact on perceived level of cohesion. Results indicate that occurrence of laughter and interruption are higher in high cohesive segments. We also observe that, dialogue acts and head nods did not have an impact on the level of cohesion by itself. However, when combined there was an impact on the perceived level of cohesion. Overall, the analysis shows that multimodal cues are crucial for accurate analysis of group cohesion.",
language = "English",
ISBN = "979-10-95546-34-4",
}
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<namePart type="given">Sara</namePart>
<namePart type="family">Goggi</namePart>
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<namePart type="given">Hitoshi</namePart>
<namePart type="family">Isahara</namePart>
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<abstract>Group cohesion is an emergent phenomenon that describes the tendency of the group members’ shared commitment to group tasks and the interpersonal attraction among them. This paper presents a multimodal analysis of group cohesion using a corpus of multi-party interactions. We utilize 16 two-minute segments annotated with cohesion from the AMI corpus. We define three layers of modalities: non-verbal social cues, dialogue acts and interruptions. The initial analysis is performed at the individual level and later, we combine the different modalities to observe their impact on perceived level of cohesion. Results indicate that occurrence of laughter and interruption are higher in high cohesive segments. We also observe that, dialogue acts and head nods did not have an impact on the level of cohesion by itself. However, when combined there was an impact on the perceived level of cohesion. Overall, the analysis shows that multimodal cues are crucial for accurate analysis of group cohesion.</abstract>
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%0 Conference Proceedings
%T Multimodal Analysis of Cohesion in Multi-party Interactions
%A Bangalore Kantharaju, Reshmashree
%A Langlet, Caroline
%A Barange, Mukesh
%A Clavel, Chloé
%A Pelachaud, Catherine
%Y Calzolari, Nicoletta
%Y Béchet, Frédéric
%Y Blache, Philippe
%Y Choukri, Khalid
%Y Cieri, Christopher
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Isahara, Hitoshi
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Hélène
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Twelfth Language Resources and Evaluation Conference
%D 2020
%8 May
%I European Language Resources Association
%C Marseille, France
%@ 979-10-95546-34-4
%G English
%F bangalore-kantharaju-etal-2020-multimodal
%X Group cohesion is an emergent phenomenon that describes the tendency of the group members’ shared commitment to group tasks and the interpersonal attraction among them. This paper presents a multimodal analysis of group cohesion using a corpus of multi-party interactions. We utilize 16 two-minute segments annotated with cohesion from the AMI corpus. We define three layers of modalities: non-verbal social cues, dialogue acts and interruptions. The initial analysis is performed at the individual level and later, we combine the different modalities to observe their impact on perceived level of cohesion. Results indicate that occurrence of laughter and interruption are higher in high cohesive segments. We also observe that, dialogue acts and head nods did not have an impact on the level of cohesion by itself. However, when combined there was an impact on the perceived level of cohesion. Overall, the analysis shows that multimodal cues are crucial for accurate analysis of group cohesion.
%U https://aclanthology.org/2020.lrec-1.63
%P 498-507
Markdown (Informal)
[Multimodal Analysis of Cohesion in Multi-party Interactions](https://aclanthology.org/2020.lrec-1.63) (Bangalore Kantharaju et al., LREC 2020)
ACL
- Reshmashree Bangalore Kantharaju, Caroline Langlet, Mukesh Barange, Chloé Clavel, and Catherine Pelachaud. 2020. Multimodal Analysis of Cohesion in Multi-party Interactions. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 498–507, Marseille, France. European Language Resources Association.