We present WoNoWa, a novel multi-modal dataset of small group interactions in collaborative tasks. The dataset is explicitly designed to elicit and to study over time a Transactive Memory System (TMS), a group's emergent state characterizing the group's meta-knowledge about "who knows what". A rich set of automatic features and manual annotations, extracted from the collected audio-visual data, is available on request for research purposes. Features include individual descriptors (e.g., position, Quantity of Motion, speech activity) and group descriptors (e.g., F-formations). Additionally, participants' self-assessments are available. Preliminary results from exploratory analyses show that the WoNoWa design allowed groups to develop a TMS that increased across the tasks. These results encourage the use of the WoNoWa dataset for a better understanding of the relationship between behavioural patterns and TMS, that in turn could help to improve group performance.

The WoNoWa Dataset: Investigating the Transactive Memory System in Small Group Interactions / Biancardi, Beatrice; Maisonnave-Couterou, Lou; Renault, Pierrick; Ravenet, Brian; Mancini, Maurizio; Varni, Giovanna. - (2020), pp. 528-537. ( 22nd ACM International Conference on Multimodal Interaction, ICMI 2020 Virtual Event Netherlands 25-29 October 2020) [10.1145/3382507.3418843].

The WoNoWa Dataset: Investigating the Transactive Memory System in Small Group Interactions

Giovanna Varni
2020-01-01

Abstract

We present WoNoWa, a novel multi-modal dataset of small group interactions in collaborative tasks. The dataset is explicitly designed to elicit and to study over time a Transactive Memory System (TMS), a group's emergent state characterizing the group's meta-knowledge about "who knows what". A rich set of automatic features and manual annotations, extracted from the collected audio-visual data, is available on request for research purposes. Features include individual descriptors (e.g., position, Quantity of Motion, speech activity) and group descriptors (e.g., F-formations). Additionally, participants' self-assessments are available. Preliminary results from exploratory analyses show that the WoNoWa design allowed groups to develop a TMS that increased across the tasks. These results encourage the use of the WoNoWa dataset for a better understanding of the relationship between behavioural patterns and TMS, that in turn could help to improve group performance.
2020
ICMI'20: Proceedings of the 2020 International Conference on Multimodal Interaction
New York, NY, United States
Association for Computing Machinery, New York, NY, United States
9781450375818
Biancardi, Beatrice; Maisonnave-Couterou, Lou; Renault, Pierrick; Ravenet, Brian; Mancini, Maurizio; Varni, Giovanna
The WoNoWa Dataset: Investigating the Transactive Memory System in Small Group Interactions / Biancardi, Beatrice; Maisonnave-Couterou, Lou; Renault, Pierrick; Ravenet, Brian; Mancini, Maurizio; Varni, Giovanna. - (2020), pp. 528-537. ( 22nd ACM International Conference on Multimodal Interaction, ICMI 2020 Virtual Event Netherlands 25-29 October 2020) [10.1145/3382507.3418843].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/365583
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