8. Dynamic Networks and Behavior: Separating Selection from Influence

Steglich, Christian; Snijders, Tom A. B.; Pearson, Michael

doi:10.1111/j.1467-9531.2010.01225.x

Cited by 809 publications

(941 citation statements)

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“…Complete descriptions of this method are given by Snijders, Steglich, and colleagues. [39][40][41] This approach affords majoradvantages over those based in classic regression analysis. The first of these is that stochastic actor-based methods allow researchers to directly model the complex dependencies between actors (ie, individuals) in a network.…”

Section: Social Network Data Analysismentioning

confidence: 99%

“…40 Inclusion of such network structural properties in the modeling of socially mediated phenomena represents a notable advancement in methodological rigor in that such structural properties (ie, statistical nonindependence between cases), when neglected, have been shown to lead to biased results. 40,41 Of particular interest in this study is the ability of stochastic actor-based modeling procedures to disentangle the twin forces of selection and influence. Selection refers to factors observed in our data that may influence a child' s friendship decision-making; these factors include structural properties such as those just named, but also may include actor attributes such as physical activity level, obesity status, gender, age similarity, etc.…”

Section: Social Network Data Analysismentioning

confidence: 99%

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The Distribution of Physical Activity in an After-school Friendship Network

2012

PEDIATRICS

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WHAT'S KNOWN ON THIS SUBJECT: New, effective approaches to obesity prevention are urgently needed. Social network interventions warrant our attention. Social networks play a significant role in adult and adolescent obesity. The role of social networks in pediatric obesity has not been examined. WHAT THIS STUDY ADDS:Afterschool friendship ties play a critical role in setting physical activity patterns in children as young as 5 to 12 years. Children' s activity levels can be changed by the activity level of their social network during a 12-week afterschool program. abstract OBJECTIVE: To examine whether a child' s friendship network in an afterschool program influences his/her physical activity.METHODS: Three waves of data were collected from school-aged children participating in aftercare (n = 81; mean [SD] age, 7.96 [1.74] years; 40% African American, 39% white, and 19% Latino) a name generator survey was used to map each child' s social network, and accelerometers were used to measure physical activity. We applied stochastic actor-based modeling for social networks and behavior.RESULTS: Children did not form or dissolve friendships based on physical activity levels, but existing friendships heavily influenced children' s level of physical activity. The strongest influence on the amount of time children spent in moderate-to-vigorous activity in the afterschool hours was the activity level of their immediate friends. Children consistently made adjustments to their activity levels of 10% or more to emulate the activity levels of their peers (odds ratio [OR] = 6.89, P , .01). Age (OR = 0.92, P , .10) and obesity status (OR = 0.66, P , .10) had marginally significant and relatively small direct effects on the activity. Gender had no direct effect on activity. CONCLUSIONS:These results suggest that friendship ties play a critical role in setting physical activity patterns in children as young as 5 to 12 years. Children' s activity levels can be increased, decreased, or stabilized depending on the activity level of their immediate social network during a 12-week afterschool program. Network-based interventions hold the potential to produce clinically significant changes to children' s physical activity.

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Section: Social Network Data Analysismentioning

confidence: 99%

Section: Social Network Data Analysismentioning

confidence: 99%

The Distribution of Physical Activity in an After-school Friendship Network

2012

PEDIATRICS

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“…We have chosen to base our dynamic empirical analysis on the stochastic actor-oriented model of Snijders et al (2010). While we considered using the matched sample framework of Aral et al (2009), it is better suited for larger networks where node homophily rather than new tie formation is the alternative explanation for influence-based diffusion.…”

Section: The Co-evolution Of Democracy Trade Network and Digital Acmentioning

confidence: 99%

Digital access, political networks and the diffusion of democracy

Rhue

Sundararajan

2014

Social Networks

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Abstract:We examine the effects of digital access on the prevalence of democracy and its diffusion via geographical and trade networks across 152 countries between 2000 and 2008. Although civil liberties and media freedom show a consistently positive relationship with different forms of digital access, our dynamic models that allow co-evolution of digital access, democracy and trade tie formation suggest that high mobile penetration has a more significant impact on civil liberties than Internet access does, and may also increase a country's "susceptibility" to democratic changes in neighboring nations. We explore possible drivers of these empirical findings, discussing some social and political implications.

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“…Thus, for instance, in the cases of homophily (Lazarsfeld & Merton, 1964, McPherson et al , 2001 or focus constraint (Feld, 2000), cultural attributes and actors' attitudes were studied as predictors of structure (e.g., Robins et al , 2001bRobins et al , , 2001a. Furthermore, in other formal studies, structural ties were taken as predictors of cultural attributes and actors' attitudes (cf., Robins et al , 2001a; relevant statistical approaches for both cases are discussed by Robins et al , 2007, Steglich et al , 2007.…”

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confidence: 99%

Boudourides, Why and how culture matters in community interorganizational structure

Boudourides¹

2017

Preprint

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ABSTRACT. Our aim here is to plead for the significance of cultural considerations of overlapping inter-attitudinal patterns right next to well established structural considerations of interorganizational networks based on overlapping membership patterns. In particular, we examine how the analytic methodological incorporation of cultural attributes or attitudes might enhance our understanding of structural community categorizations in interorganizational networks. For this purpose, we analyze data of the International Peace Protest Survey (IPPS) on the world-wide peace protests of February, 15, 2003, in order to manifest the added value offered by the consideration of the culturestructure duality in participation studies.

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8. Dynamic Networks and Behavior: Separating Selection from Influence

Cited by 809 publications

References 79 publications

The Distribution of Physical Activity in an After-school Friendship Network

The Distribution of Physical Activity in an After-school Friendship Network

Digital access, political networks and the diffusion of democracy

Boudourides, Why and how culture matters in community interorganizational structure

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