Computational analysis of social contagion and homophily based on an adaptive social network model

Guusje Boomgaard; Falko Lavitt; J. Treur

doi:10.1007/978-3-030-01129-1_6

Computational analysis of social contagion and homophily based on an adaptive social network model

Guusje Boomgaard, Falko Lavitt, J. Treur^*

^*Corresponding author for this work

Computer Science

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

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Abstract

This study combined the Social Science principles of homophily and social contagion within an approach to adaptive network modeling. The introduced adaptive temporal-causal network model incorporates both principles. This model was used to analyse an empirical data set concerning delinquency behaviour data among secondary school students. A mathematical analysis provided more in depth insight in the behavior of the model.

Original language	English
Title of host publication	Social Informatics
Subtitle of host publication	10th International Conference, SocInfo 2018, St. Petersburg, Russia, September 25-28, 2018, Proceedings, Part I
Editors	Olessia Koltsova, Dmitry I. Ignatov, Steffen Staab
Publisher	Springer
Pages	86-101
Number of pages	16
Volume	1
ISBN (Electronic)	9783030011284
ISBN (Print)	9783030011291
DOIs	https://doi.org/10.1007/978-3-030-01129-1_6
Publication status	Published - 2018
Event	10th International Conference on Social Informatics, SocInfo'18 - Saint Petersburg, Russian Federation Duration: 25 Sept 2018 → 28 Sept 2018 Conference number: 10 https://socinfo2018.hse.ru/

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11185 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th International Conference on Social Informatics, SocInfo'18
Abbreviated title	SocInfo
Country/Territory	Russian Federation
City	Saint Petersburg
Period	25/09/18 → 28/09/18
Internet address	https://socinfo2018.hse.ru/

Keywords

Homophily
Social contagion
Social network

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/978-3-030-01129-1_6

Computational analysis of social contagion and homophily based on an adaptive social network modelFinal published version, 2.49 MBLicence: Article 25fa Dutch Copyright Act

https://www.researchgate.net/publication/326625528_Computational_Analysis_of_Social_Contagion_and_Homophily_Based_on_an_Adaptive_Social_Network_Model

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Boomgaard, G., Lavitt, F., & Treur, J. (2018). Computational analysis of social contagion and homophily based on an adaptive social network model. In O. Koltsova, D. I. Ignatov, & S. Staab (Eds.), Social Informatics: 10th International Conference, SocInfo 2018, St. Petersburg, Russia, September 25-28, 2018, Proceedings, Part I (Vol. 1, pp. 86-101). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11185 LNCS). Springer. https://doi.org/10.1007/978-3-030-01129-1_6

Boomgaard, Guusje ; Lavitt, Falko ; Treur, J. / Computational analysis of social contagion and homophily based on an adaptive social network model. Social Informatics: 10th International Conference, SocInfo 2018, St. Petersburg, Russia, September 25-28, 2018, Proceedings, Part I. editor / Olessia Koltsova ; Dmitry I. Ignatov ; Steffen Staab. Vol. 1 Springer, 2018. pp. 86-101 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Computational analysis of social contagion and homophily based on an adaptive social network model",

abstract = "This study combined the Social Science principles of homophily and social contagion within an approach to adaptive network modeling. The introduced adaptive temporal-causal network model incorporates both principles. This model was used to analyse an empirical data set concerning delinquency behaviour data among secondary school students. A mathematical analysis provided more in depth insight in the behavior of the model.",

keywords = "Homophily, Social contagion, Social network",

author = "Guusje Boomgaard and Falko Lavitt and J. Treur",

year = "2018",

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editor = "Olessia Koltsova and Ignatov, \{Dmitry I.\} and Steffen Staab",

booktitle = "Social Informatics",

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Boomgaard, G, Lavitt, F & Treur, J 2018, Computational analysis of social contagion and homophily based on an adaptive social network model. in O Koltsova, DI Ignatov & S Staab (eds), Social Informatics: 10th International Conference, SocInfo 2018, St. Petersburg, Russia, September 25-28, 2018, Proceedings, Part I. vol. 1, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11185 LNCS, Springer, pp. 86-101, 10th International Conference on Social Informatics, SocInfo'18, Saint Petersburg, Russian Federation, 25/09/18. https://doi.org/10.1007/978-3-030-01129-1_6

Computational analysis of social contagion and homophily based on an adaptive social network model. / Boomgaard, Guusje; Lavitt, Falko; Treur, J.
Social Informatics: 10th International Conference, SocInfo 2018, St. Petersburg, Russia, September 25-28, 2018, Proceedings, Part I. ed. / Olessia Koltsova; Dmitry I. Ignatov; Steffen Staab. Vol. 1 Springer, 2018. p. 86-101 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11185 LNCS).

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

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T1 - Computational analysis of social contagion and homophily based on an adaptive social network model

AU - Boomgaard, Guusje

AU - Lavitt, Falko

AU - Treur, J.

N1 - Conference code: 10

PY - 2018

Y1 - 2018

N2 - This study combined the Social Science principles of homophily and social contagion within an approach to adaptive network modeling. The introduced adaptive temporal-causal network model incorporates both principles. This model was used to analyse an empirical data set concerning delinquency behaviour data among secondary school students. A mathematical analysis provided more in depth insight in the behavior of the model.

AB - This study combined the Social Science principles of homophily and social contagion within an approach to adaptive network modeling. The introduced adaptive temporal-causal network model incorporates both principles. This model was used to analyse an empirical data set concerning delinquency behaviour data among secondary school students. A mathematical analysis provided more in depth insight in the behavior of the model.

KW - Homophily

KW - Social contagion

KW - Social network

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VL - 1

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 86

EP - 101

BT - Social Informatics

A2 - Koltsova, Olessia

A2 - Ignatov, Dmitry I.

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T2 - 10th International Conference on Social Informatics, SocInfo'18

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Boomgaard G, Lavitt F, Treur J. Computational analysis of social contagion and homophily based on an adaptive social network model. In Koltsova O, Ignatov DI, Staab S, editors, Social Informatics: 10th International Conference, SocInfo 2018, St. Petersburg, Russia, September 25-28, 2018, Proceedings, Part I. Vol. 1. Springer. 2018. p. 86-101. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Epub 2018 Sept 20. doi: 10.1007/978-3-030-01129-1_6

Computational analysis of social contagion and homophily based on an adaptive social network model

Abstract

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Conference

Keywords

UN SDGs

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