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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.


Schema representing which information was obtained from which dataset
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Fig2: Schema representing which information was obtained from which dataset

Mentions: Two datasets are used to estimate the modelĀ (Fig. 2). The first data set is from a national travel survey (MON) of The Netherlands collected by the Ministry of Transport (Ministry of Transport 2009). It is a travel-diary panel survey. For this study we have taken the latest version of 2009. It is a large sample (in 2009, approximately 30,000 individuals) representative of the Dutch population. The second dataset was collected to obtain information about the dynamics of personal social networks. A questionnaire was designed for an event-based retrospective survey where information was collected about changes in social networks of persons due to major life-cycle events (Sharmeen 2015). The first dataset is used to obtain a sample of the population. The sample is used to provide negative observations, i.e. the persons with whom no tie exists, for each individual. Although in principle all persons of the entire population with whom the person does not have a friendship relationship constitute negative observations, it has been shown that a sample suffices to obtain reliable estimates (Arentze et al. 2013) except for the constants1. The second dataset provides the key information to estimate a friendship model that allows us to predict probabilities of ego-alter tie dynamics.


Predicting the evolution of social networks with life cycle events.

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

Schema representing which information was obtained from which dataset
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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

Fig2: Schema representing which information was obtained from which dataset
Mentions: Two datasets are used to estimate the modelĀ (Fig. 2). The first data set is from a national travel survey (MON) of The Netherlands collected by the Ministry of Transport (Ministry of Transport 2009). It is a travel-diary panel survey. For this study we have taken the latest version of 2009. It is a large sample (in 2009, approximately 30,000 individuals) representative of the Dutch population. The second dataset was collected to obtain information about the dynamics of personal social networks. A questionnaire was designed for an event-based retrospective survey where information was collected about changes in social networks of persons due to major life-cycle events (Sharmeen 2015). The first dataset is used to obtain a sample of the population. The sample is used to provide negative observations, i.e. the persons with whom no tie exists, for each individual. Although in principle all persons of the entire population with whom the person does not have a friendship relationship constitute negative observations, it has been shown that a sample suffices to obtain reliable estimates (Arentze et al. 2013) except for the constants1. The second dataset provides the key information to estimate a friendship model that allows us to predict probabilities of ego-alter tie dynamics.

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.