Physical activity contagion and homophily in an adaptive social network model

Marit van Dijk, Jan Treur

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

Regular physical activity contributes to higher levels of well-being, healthy aging and prevention of several chronic diseases such as depression. To establish or change behaviours concerning physical activity, social contagion may play a role. The aim of this study was to model the contagion of physical activity based on empirical Twitter data and to assess the role of homophily within this contagion. To model the contagion of physical activity, an adaptive temporal-causal network model was designed, and accordingly, the parameters of the model were tuned using empirical data obtained from Twitter. Two variants of the adaptive temporal-causal network model were created, in which one calculated the weights of the connections between the nodes based on follow relations on Twitter, while in the other the connection weights were modulated by the homophily principle. The results indicate that within the considered social network of already active persons homophily does not play an important role in the physical activity behaviour.

LanguageEnglish
Title of host publicationComputational Collective Intelligence
Subtitle of host publication10th International Conference, ICCCI 2018, Proceedings
EditorsNgoc Thanh Nguyen, Elias Pimenidis, Zaheer Khan, Bogdan Trawinski
PublisherSpringer/Verlag
Pages87-98
Number of pages12
Volume1
ISBN (Electronic)9783319984438
ISBN (Print)9783319984421
DOIs
StatePublished - 2018
Event10th International Conference on Computational Collective Intelligence, ICCCI 2018 - Bristol, United Kingdom
Duration: 5 Sep 20187 Sep 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11055 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Conference on Computational Collective Intelligence, ICCCI 2018
CountryUnited Kingdom
CityBristol
Period5/09/187/09/18

Fingerprint

Contagion
Social Networks
Network Model
Causal Model
Chronic Disease
Person
Aging of materials
Model
Vertex of a graph

Cite this

van Dijk, M., & Treur, J. (2018). Physical activity contagion and homophily in an adaptive social network model. In N. T. Nguyen, E. Pimenidis, Z. Khan, & B. Trawinski (Eds.), Computational Collective Intelligence: 10th International Conference, ICCCI 2018, Proceedings (Vol. 1, pp. 87-98). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11055 LNAI). Springer/Verlag. DOI: 10.1007/978-3-319-98443-8_9
van Dijk, Marit ; Treur, Jan. / Physical activity contagion and homophily in an adaptive social network model. Computational Collective Intelligence: 10th International Conference, ICCCI 2018, Proceedings. editor / Ngoc Thanh Nguyen ; Elias Pimenidis ; Zaheer Khan ; Bogdan Trawinski. Vol. 1 Springer/Verlag, 2018. pp. 87-98 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{91bc7e1eae2b42e9b9df25dccb72be17,
title = "Physical activity contagion and homophily in an adaptive social network model",
abstract = "Regular physical activity contributes to higher levels of well-being, healthy aging and prevention of several chronic diseases such as depression. To establish or change behaviours concerning physical activity, social contagion may play a role. The aim of this study was to model the contagion of physical activity based on empirical Twitter data and to assess the role of homophily within this contagion. To model the contagion of physical activity, an adaptive temporal-causal network model was designed, and accordingly, the parameters of the model were tuned using empirical data obtained from Twitter. Two variants of the adaptive temporal-causal network model were created, in which one calculated the weights of the connections between the nodes based on follow relations on Twitter, while in the other the connection weights were modulated by the homophily principle. The results indicate that within the considered social network of already active persons homophily does not play an important role in the physical activity behaviour.",
author = "{van Dijk}, Marit and Jan Treur",
year = "2018",
doi = "10.1007/978-3-319-98443-8_9",
language = "English",
isbn = "9783319984421",
volume = "1",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer/Verlag",
pages = "87--98",
editor = "Nguyen, {Ngoc Thanh} and Elias Pimenidis and Zaheer Khan and Bogdan Trawinski",
booktitle = "Computational Collective Intelligence",

}

van Dijk, M & Treur, J 2018, Physical activity contagion and homophily in an adaptive social network model. in NT Nguyen, E Pimenidis, Z Khan & B Trawinski (eds), Computational Collective Intelligence: 10th International Conference, ICCCI 2018, Proceedings. vol. 1, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11055 LNAI, Springer/Verlag, pp. 87-98, 10th International Conference on Computational Collective Intelligence, ICCCI 2018, Bristol, United Kingdom, 5/09/18. DOI: 10.1007/978-3-319-98443-8_9

Physical activity contagion and homophily in an adaptive social network model. / van Dijk, Marit; Treur, Jan.

Computational Collective Intelligence: 10th International Conference, ICCCI 2018, Proceedings. ed. / Ngoc Thanh Nguyen; Elias Pimenidis; Zaheer Khan; Bogdan Trawinski. Vol. 1 Springer/Verlag, 2018. p. 87-98 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11055 LNAI).

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

TY - GEN

T1 - Physical activity contagion and homophily in an adaptive social network model

AU - van Dijk,Marit

AU - Treur,Jan

PY - 2018

Y1 - 2018

N2 - Regular physical activity contributes to higher levels of well-being, healthy aging and prevention of several chronic diseases such as depression. To establish or change behaviours concerning physical activity, social contagion may play a role. The aim of this study was to model the contagion of physical activity based on empirical Twitter data and to assess the role of homophily within this contagion. To model the contagion of physical activity, an adaptive temporal-causal network model was designed, and accordingly, the parameters of the model were tuned using empirical data obtained from Twitter. Two variants of the adaptive temporal-causal network model were created, in which one calculated the weights of the connections between the nodes based on follow relations on Twitter, while in the other the connection weights were modulated by the homophily principle. The results indicate that within the considered social network of already active persons homophily does not play an important role in the physical activity behaviour.

AB - Regular physical activity contributes to higher levels of well-being, healthy aging and prevention of several chronic diseases such as depression. To establish or change behaviours concerning physical activity, social contagion may play a role. The aim of this study was to model the contagion of physical activity based on empirical Twitter data and to assess the role of homophily within this contagion. To model the contagion of physical activity, an adaptive temporal-causal network model was designed, and accordingly, the parameters of the model were tuned using empirical data obtained from Twitter. Two variants of the adaptive temporal-causal network model were created, in which one calculated the weights of the connections between the nodes based on follow relations on Twitter, while in the other the connection weights were modulated by the homophily principle. The results indicate that within the considered social network of already active persons homophily does not play an important role in the physical activity behaviour.

UR - http://www.scopus.com/inward/record.url?scp=85053181596&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85053181596&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-98443-8_9

DO - 10.1007/978-3-319-98443-8_9

M3 - Conference contribution

SN - 9783319984421

VL - 1

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

SP - 87

EP - 98

BT - Computational Collective Intelligence

PB - Springer/Verlag

ER -

van Dijk M, Treur J. Physical activity contagion and homophily in an adaptive social network model. In Nguyen NT, Pimenidis E, Khan Z, Trawinski B, editors, Computational Collective Intelligence: 10th International Conference, ICCCI 2018, Proceedings. Vol. 1. Springer/Verlag. 2018. p. 87-98. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Available from, DOI: 10.1007/978-3-319-98443-8_9