Switching In and Out of Sync:A Controlled Adaptive Network Model of Transition Dynamics in the Effects of Interpersonal Synchrony on Affiliation

Autor: Hendrikse, Sophie C.F., Treur, Jan, Wilderjans, Tom F., Dikker, Suzanne, Koole, Sander L., Cherifi, Hocine, Mantegna, Rosario Nunzio, Rocha, Luis M., Cherifi, Chantal, Micciche, Salvatore
Přispěvatelé: Cherifi, Hocine, Mantegna, Rosario Nunzio, Rocha, Luis M., Cherifi, Chantal, Micciche, Salvatore, Clinical Psychology, Computer Science, Social AI, APH - Mental Health
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Hendrikse, S C F, Treur, J, Wilderjans, T F, Dikker, S & Koole, S L 2023, Switching In and Out of Sync : A Controlled Adaptive Network Model of Transition Dynamics in the Effects of Interpersonal Synchrony on Affiliation . in H Cherifi, R N Mantegna, L M Rocha, C Cherifi & S Micciche (eds), Complex Networks and Their Applications XI : Proceedings of The Eleventh International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2022 — Volume 2 . vol. 2, Studies in Computational Intelligence, vol. 1078, Springer Science and Business Media Deutschland GmbH, pp. 81-95, 11th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2022, Palermo, Italy, 8/11/22 . https://doi.org/10.1007/978-3-031-21131-7_7
Complex Networks and Their Applications XI: Proceedings of The Eleventh International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2022 — Volume 2, 2, 81-95
Complex Networks and Their Applications XI ISBN: 9783031211300
DOI: 10.1007/978-3-031-21131-7_7
Popis: Interpersonal synchrony is associated with better interpersonal affiliation. No matter how well-affiliated people are, interruptions or transitions in synchrony rebound to occur. One might intuitively expect that transitions in synchrony negatively affect affiliation or liking. Empirical evidence, however, suggests that time periods with interruptions in synchrony may favor affiliation or liking even more than time periods without interruptions in synchrony. This paper introduces a controlled adaptive network model to explain how persons’ affiliation might benefit from transitions in synchrony over and above mean levels of synchrony. The adaptive network model was evaluated in a series of simulation experiments for two persons with a setup in which a number of scenarios were encountered in different (time) episodes. Our controlled adaptive network model may serve as a foundation for more realistic virtual agents with regard to synchrony transitions and their role in affiliation.
Databáze: OpenAIRE
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