We discuss a preliminary investigation on the feasibility of inferring traits of social participation from the observable behaviour of individuals involved in dyadic interactions. Trait inference relies on a stochastic model of the dynamics occurring in the individual core affect state-space. Results obtained on a publicly available interaction dataset are presented and examined.
Social traits from stochastic paths in the core affect space / G. Boccignone, V. Cuculo, A. D'Amelio, R. Lanzarotti - In: PervasiveHealth'19 : ProceedingsPrima edizione. - [s.l] : ACM, 2019. - ISBN 9781450361262. - pp. 314-319 (( Intervento presentato al 13. convegno EAI International Conference on Pervasive Computing Technologies for Healthcare tenutosi a Trento nel 2019.
Social traits from stochastic paths in the core affect space
G. BoccignonePrimo
Membro del Collaboration Group
;V. Cuculo
Secondo
Membro del Collaboration Group
;A. D'AmelioPenultimo
Membro del Collaboration Group
;R. LanzarottiUltimo
Membro del Collaboration Group
2019
Abstract
We discuss a preliminary investigation on the feasibility of inferring traits of social participation from the observable behaviour of individuals involved in dyadic interactions. Trait inference relies on a stochastic model of the dynamics occurring in the individual core affect state-space. Results obtained on a publicly available interaction dataset are presented and examined.File | Dimensione | Formato | |
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