Abstract
| Language | English |
|---|---|
| Title of host publication | Complex Networks VIII. CompleNet 2017. |
| Publisher | Springer/Verlag |
| Pages | 213-223 |
| ISBN (Electronic) | 978-3-319-54241-6 |
| ISBN (Print) | 978-3-319-54240-9 |
| DOIs | |
| State | Published - 21 Mar 2017 |
Publication series
| Name | Springer Proceedings in Complexity |
|---|
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Keywords
- Computational modeling
- Social contagion
- Validation
- Physical activity
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Explaining Changes in Physical Activity Through a Computational Model of Social Contagion. / Mollee, J.S.; Fernandes de Mello Araujo, E.; Manzoor, A.; van Halteren, A.T.; Klein, M.C.A.
Complex Networks VIII. CompleNet 2017.. Springer/Verlag, 2017. p. 213-223 (Springer Proceedings in Complexity).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Explaining Changes in Physical Activity Through a Computational Model of Social Contagion
AU - Mollee,J.S.
AU - Fernandes de Mello Araujo,E.
AU - Manzoor,A.
AU - van Halteren,A.T.
AU - Klein,M.C.A.
PY - 2017/3/21
Y1 - 2017/3/21
N2 - Social processes play a key role in health behaviour. Understanding the underlying mechanisms of such processes is important when designing health interventions with a social component. In this work, we apply a computational model of social contagion to a data set of 2,472 users of a physical activity promotion program. We compare this model’s predictions to the predictions of a simple linear model that has been derived by a regression analysis. The results show that the social contagion model performs better at describing the pattern seen in the empirical data than the linear model, indicating that some of the dynamics of the physical activity levels in the network can be explained by social contagion processes.
AB - Social processes play a key role in health behaviour. Understanding the underlying mechanisms of such processes is important when designing health interventions with a social component. In this work, we apply a computational model of social contagion to a data set of 2,472 users of a physical activity promotion program. We compare this model’s predictions to the predictions of a simple linear model that has been derived by a regression analysis. The results show that the social contagion model performs better at describing the pattern seen in the empirical data than the linear model, indicating that some of the dynamics of the physical activity levels in the network can be explained by social contagion processes.
KW - Computational modeling
KW - Social contagion
KW - Validation
KW - Physical activity
U2 - 10.1007/978-3-319-54241-6_19
DO - 10.1007/978-3-319-54241-6_19
M3 - Conference contribution
SN - 978-3-319-54240-9
T3 - Springer Proceedings in Complexity
SP - 213
EP - 223
BT - Complex Networks VIII. CompleNet 2017.
PB - Springer/Verlag
ER -