TY - JOUR

T1 - Dose–response functions and surrogate models for exploring social contagion in the Copenhagen Networks Study

AU - Donges, Jonathan F.

AU - Lochner, Jakob H.

AU - Kitzmann, Niklas H.

AU - Heitzig, Jobst

AU - Lehmann, Sune

AU - Wiedermann, Marc

AU - Vollmer, Jürgen

N1 - Funding Information: The authors would like to thank Franziska Gutmann and Michaela Schinkoeth of the Sport and Exercise Psychology research group at University of Potsdam for a helpful discussion. JFD, JH, JHL and MW are thankful for financial support by the Leibniz Association (project DominoES). JFD acknowledges support from the European Research Council project Earth Resilience in the Anthropocene (743080 ERA). NHK is grateful to the Geo.X Young Academy for financial support. SL acknowledges support by the Danish Research Council and the Villum Foundation. Publisher Copyright: © 2021, The Author(s).

PY - 2021/10

Y1 - 2021/10

N2 - Spreading dynamics and complex contagion processes on networks are important mechanisms underlying the emergence of critical transitions, tipping points and other non-linear phenomena in complex human and natural systems. Increasing amounts of temporal network data are now becoming available to study such spreading processes of behaviours, opinions, ideas, diseases and innovations to test hypotheses regarding their specific properties. To this end, we here present a methodology based on dose–response functions and hypothesis testing using surrogate data models that randomise most aspects of the empirical data while conserving certain structures relevant to contagion, group or homophily dynamics. We demonstrate this methodology for synthetic temporal network data of spreading processes generated by the adaptive voter model. Furthermore, we apply it to empirical temporal network data from the Copenhagen Networks Study. This data set provides a physically-close-contact network between several hundreds of university students participating in the study over the course of 3 months. We study the potential spreading dynamics of the health-related behaviour “regularly going to the fitness studio” on this network. Based on a hierarchy of surrogate data models, we find that our method neither provides significant evidence for an influence of a dose–response-type network spreading process in this data set, nor significant evidence for homophily. The empirical dynamics in exercise behaviour are likely better described by individual features such as the disposition towards the behaviour, and the persistence to maintain it, as well as external influences affecting the whole group, and the non-trivial network structure. The proposed methodology is generic and promising also for applications to other temporal network data sets and traits of interest.

AB - Spreading dynamics and complex contagion processes on networks are important mechanisms underlying the emergence of critical transitions, tipping points and other non-linear phenomena in complex human and natural systems. Increasing amounts of temporal network data are now becoming available to study such spreading processes of behaviours, opinions, ideas, diseases and innovations to test hypotheses regarding their specific properties. To this end, we here present a methodology based on dose–response functions and hypothesis testing using surrogate data models that randomise most aspects of the empirical data while conserving certain structures relevant to contagion, group or homophily dynamics. We demonstrate this methodology for synthetic temporal network data of spreading processes generated by the adaptive voter model. Furthermore, we apply it to empirical temporal network data from the Copenhagen Networks Study. This data set provides a physically-close-contact network between several hundreds of university students participating in the study over the course of 3 months. We study the potential spreading dynamics of the health-related behaviour “regularly going to the fitness studio” on this network. Based on a hierarchy of surrogate data models, we find that our method neither provides significant evidence for an influence of a dose–response-type network spreading process in this data set, nor significant evidence for homophily. The empirical dynamics in exercise behaviour are likely better described by individual features such as the disposition towards the behaviour, and the persistence to maintain it, as well as external influences affecting the whole group, and the non-trivial network structure. The proposed methodology is generic and promising also for applications to other temporal network data sets and traits of interest.

U2 - 10.1140/epjs/s11734-021-00279-7

DO - 10.1140/epjs/s11734-021-00279-7

M3 - Journal article

C2 - 34611486

AN - SCOPUS:85115800983

VL - 230

SP - 3311

EP - 3334

JO - European Physical Journal. Special Topics

JF - European Physical Journal. Special Topics

SN - 1951-6355

IS - 16-17

ER -