An Adaptive Computational Network Model for Multi-Emotional Social Interaction

Ramona Roller; Suzan Q. Blommestijn; J. Treur

doi:10.1007/978-3-319-72150-7_63

An Adaptive Computational Network Model for Multi-Emotional Social Interaction

Ramona Roller, Suzan Q. Blommestijn, J. Treur

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

The study reported in this paper investigates an adaptive temporal-causal
network-model for emotion contagion. The dynamic network principles of emotion contagion and the adaptive principles of homophily and Hebbian learning were used to simulate the change in multiple emotions and social interactions over time. It is shown that the model can be successfully initialised with Twitter data, while parameters were optimised via simulated annealing. Moreover, an exploratory analysis for model validation and applications provided insights in the model's potentials and limitations. The study advances the existing methodology of modelling the social contagion of multiple emotions in a context where also the social network evolves over time.

Original language	English
Title of host publication	Complex Networks & Their Applications VI
Subtitle of host publication	Proceedings of Complex Networks 2017 (The Sixth International Conference on Complex Networks and Their Applications)
Editors	Chantal Cherifi, Hocine Cherifi, Márton Karsai, Mirco Musolesi
Publisher	Springer Verlag
Pages	784-796
Number of pages	13
ISBN (Electronic)	9783319721507
ISBN (Print)	9783319721491, 9783319891491
DOIs	https://doi.org/10.1007/978-3-319-72150-7_63
Publication status	Published - 2017

Publication series

Name	Studies in Computational Intelligence (SCI)
Publisher	Springer Publishers
Volume	689

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An Adaptive Computational Network Model for Multi-Emotional Social InteractionFinal published version, 973 KBLicence: Article 25fa Dutch Copyright Act

https://www.researchgate.net/publication/320685561_An_Adaptive_Computational_Network_Model_for_Multi-Emotional_Social_Interaction

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Roller, R., Blommestijn, S. Q., & Treur, J. (2017). An Adaptive Computational Network Model for Multi-Emotional Social Interaction. In C. Cherifi, H. Cherifi, M. Karsai, & M. Musolesi (Eds.), Complex Networks & Their Applications VI: Proceedings of Complex Networks 2017 (The Sixth International Conference on Complex Networks and Their Applications) (pp. 784-796). (Studies in Computational Intelligence (SCI); Vol. 689). Springer Verlag. https://doi.org/10.1007/978-3-319-72150-7_63

Roller, Ramona ; Blommestijn, Suzan Q. ; Treur, J. / An Adaptive Computational Network Model for Multi-Emotional Social Interaction. Complex Networks & Their Applications VI: Proceedings of Complex Networks 2017 (The Sixth International Conference on Complex Networks and Their Applications). editor / Chantal Cherifi ; Hocine Cherifi ; Márton Karsai ; Mirco Musolesi. Springer Verlag, 2017. pp. 784-796 (Studies in Computational Intelligence (SCI)).

@inproceedings{4e61127928a04e59b400032724b16b94,

title = "An Adaptive Computational Network Model for Multi-Emotional Social Interaction",

abstract = "The study reported in this paper investigates an adaptive temporal-causalnetwork-model for emotion contagion. The dynamic network principles of emotion contagion and the adaptive principles of homophily and Hebbian learning were used to simulate the change in multiple emotions and social interactions over time. It is shown that the model can be successfully initialised with Twitter data, while parameters were optimised via simulated annealing. Moreover, an exploratory analysis for model validation and applications provided insights in the model's potentials and limitations. The study advances the existing methodology of modelling the social contagion of multiple emotions in a context where also the social network evolves over time.",

author = "Ramona Roller and Blommestijn, {Suzan Q.} and J. Treur",

year = "2017",

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language = "English",

isbn = "9783319721491",

series = "Studies in Computational Intelligence (SCI)",

publisher = "Springer Verlag",

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Roller, R, Blommestijn, SQ & Treur, J 2017, An Adaptive Computational Network Model for Multi-Emotional Social Interaction. in C Cherifi, H Cherifi, M Karsai & M Musolesi (eds), Complex Networks & Their Applications VI: Proceedings of Complex Networks 2017 (The Sixth International Conference on Complex Networks and Their Applications). Studies in Computational Intelligence (SCI), vol. 689, Springer Verlag, pp. 784-796. https://doi.org/10.1007/978-3-319-72150-7_63

An Adaptive Computational Network Model for Multi-Emotional Social Interaction. / Roller, Ramona; Blommestijn, Suzan Q.; Treur, J.
Complex Networks & Their Applications VI: Proceedings of Complex Networks 2017 (The Sixth International Conference on Complex Networks and Their Applications). ed. / Chantal Cherifi; Hocine Cherifi; Márton Karsai; Mirco Musolesi. Springer Verlag, 2017. p. 784-796 (Studies in Computational Intelligence (SCI); Vol. 689).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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N2 - The study reported in this paper investigates an adaptive temporal-causalnetwork-model for emotion contagion. The dynamic network principles of emotion contagion and the adaptive principles of homophily and Hebbian learning were used to simulate the change in multiple emotions and social interactions over time. It is shown that the model can be successfully initialised with Twitter data, while parameters were optimised via simulated annealing. Moreover, an exploratory analysis for model validation and applications provided insights in the model's potentials and limitations. The study advances the existing methodology of modelling the social contagion of multiple emotions in a context where also the social network evolves over time.

AB - The study reported in this paper investigates an adaptive temporal-causalnetwork-model for emotion contagion. The dynamic network principles of emotion contagion and the adaptive principles of homophily and Hebbian learning were used to simulate the change in multiple emotions and social interactions over time. It is shown that the model can be successfully initialised with Twitter data, while parameters were optimised via simulated annealing. Moreover, an exploratory analysis for model validation and applications provided insights in the model's potentials and limitations. The study advances the existing methodology of modelling the social contagion of multiple emotions in a context where also the social network evolves over time.

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DO - 10.1007/978-3-319-72150-7_63

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Roller R, Blommestijn SQ, Treur J. An Adaptive Computational Network Model for Multi-Emotional Social Interaction. In Cherifi C, Cherifi H, Karsai M, Musolesi M, editors, Complex Networks & Their Applications VI: Proceedings of Complex Networks 2017 (The Sixth International Conference on Complex Networks and Their Applications). Springer Verlag. 2017. p. 784-796. (Studies in Computational Intelligence (SCI)). Epub 2017 Nov 27. doi: 10.1007/978-3-319-72150-7_63

An Adaptive Computational Network Model for Multi-Emotional Social Interaction

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