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Predicting the evolution of social networks with life cycle events.

Sharmeen F, Arentze T, Timmermans H - Transportation (Amst) (2015)

Bottom Line: Findings suggest that homophily has a strong effect on the formation of new ties.However, heterophily also plays a role in maintaining existing ties.Although the motivation of this research stems from incorporating social network dynamics in large-scale travel behaviour micro-simulation models, the research can be used in a variety of fields for similar purposes.

View Article: PubMed Central - PubMed

Affiliation: Eindhoven University of Technology, P.O. Box 513, Vertigo 8.09, 5600 MB Eindhoven, The Netherlands.

ABSTRACT

This paper presents a model of social network evolution, to predict and simulate changes in social networks induced by lifecycle events. We argue that social networks change with lifecycle events, and we extend a model of friendship selection to incorporate these dynamics of personal social networks. The model uses theories of homophily and reciprocity and is formulated in a random utility maximization framework to predict the formation of social ties between individuals in the population. It is then extended to predict the evolution of social networks in response to life cycle events. The model is estimated using attribute data of a national sample and an event-based retrospective dataset collected in 2009 and 2011 respectively. Findings suggest that homophily has a strong effect on the formation of new ties. However, heterophily also plays a role in maintaining existing ties. Although the motivation of this research stems from incorporating social network dynamics in large-scale travel behaviour micro-simulation models, the research can be used in a variety of fields for similar purposes.

No MeSH data available.


Problem definition (top diagram—no tie; choice is to make a tie or not, bottom diagram—tie exists; choice is to keep it or lose it)
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Fig1: Problem definition (top diagram—no tie; choice is to make a tie or not, bottom diagram—tie exists; choice is to keep it or lose it)

Mentions: To incorporate the dynamics induced by life cycle events in personal social networks, we model decisions of tie formation in two phases (before and after an event). In the initial phase individuals make tie-formation decisions as described by the basic model above. In the adaptation phase, an individual has two decisions to make (Fig. 1):Fig. 1


Predicting the evolution of social networks with life cycle events.

Sharmeen F, Arentze T, Timmermans H - Transportation (Amst) (2015)

Problem definition (top diagram—no tie; choice is to make a tie or not, bottom diagram—tie exists; choice is to keep it or lose it)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4585409&req=5

Fig1: Problem definition (top diagram—no tie; choice is to make a tie or not, bottom diagram—tie exists; choice is to keep it or lose it)
Mentions: To incorporate the dynamics induced by life cycle events in personal social networks, we model decisions of tie formation in two phases (before and after an event). In the initial phase individuals make tie-formation decisions as described by the basic model above. In the adaptation phase, an individual has two decisions to make (Fig. 1):Fig. 1

Bottom Line: Findings suggest that homophily has a strong effect on the formation of new ties.However, heterophily also plays a role in maintaining existing ties.Although the motivation of this research stems from incorporating social network dynamics in large-scale travel behaviour micro-simulation models, the research can be used in a variety of fields for similar purposes.

View Article: PubMed Central - PubMed

Affiliation: Eindhoven University of Technology, P.O. Box 513, Vertigo 8.09, 5600 MB Eindhoven, The Netherlands.

ABSTRACT

This paper presents a model of social network evolution, to predict and simulate changes in social networks induced by lifecycle events. We argue that social networks change with lifecycle events, and we extend a model of friendship selection to incorporate these dynamics of personal social networks. The model uses theories of homophily and reciprocity and is formulated in a random utility maximization framework to predict the formation of social ties between individuals in the population. It is then extended to predict the evolution of social networks in response to life cycle events. The model is estimated using attribute data of a national sample and an event-based retrospective dataset collected in 2009 and 2011 respectively. Findings suggest that homophily has a strong effect on the formation of new ties. However, heterophily also plays a role in maintaining existing ties. Although the motivation of this research stems from incorporating social network dynamics in large-scale travel behaviour micro-simulation models, the research can be used in a variety of fields for similar purposes.

No MeSH data available.