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Friendship Dissolution Within Social Networks Modeled Through Multilevel Event History Analysis Multivariate Behavioral Research ISSN: 0027-3171 (Print) 1532-7906 (Online) Journal homepage: http://www.tandfonline.com/loi/hmbr20 Friendship Dissolution Within Social Networks Modeled Through Multilevel Event History Analysis Danielle O. Dean, Daniel J. Bauer & Mitchell J. Prinstein To cite this article: Danielle O. Dean, Daniel J. Bauer & Mitchell J. Prinstein (2017) Friendship Dissolution Within Social Networks Modeled Through Multilevel Event History Analysis, Multivariate Behavioral Research, 52:3, 271-289, DOI: 10.1080/00273171.2016.1267605 To link to this article: http://dx.doi.org/10.1080/00273171.2016.1267605 View supplementary material Published online: 02 May 2017. Submit your article to this journal Article views: 182 View related articles View Crossmark data Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=hmbr20 Download by: [University North Carolina - Chapel Hill] Date: 07 November 2017, At: 08:19 MULTIVARIATE BEHAVIORAL RESEARCH , VOL. , NO. , – http://dx.doi.org/./.. Friendship Dissolution Within Social Networks Modeled Through Multilevel Event History Analysis Danielle O. Deana,DanielJ.Bauerb, and Mitchell J. Prinsteinc aData Group, Microsoft; bQuantitative Psychology, Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill; cClinical Psychology, Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill ABSTRACT KEYWORDS A social network perspective can bring important insight into the processes that shape human behav- Event history analysis; ior. Longitudinal social network data, measuring relations between individuals over time, has become generalized linear modeling; increasingly common—as have the methods available to analyze such data. A friendship duration multilevel modeling; social model utilizing discrete-time multilevel survival analysis with a multiple membership random effect network analysis; survival analysis structure is developed and applied here to study the processes leading to undirected friendship disso- lution within a larger social network. While the modeling framework is introduced in terms of under- standing friendship dissolution, it can be used to understand microlevel dynamics of a social network more generally. These models can be fit with standard generalized linear mixed-model software, after transforming the data to a pair-period data set. An empirical example highlights how the model can be applied to understand the processes leading to friendship dissolution between high school stu- dents, and a simulation study is used to test the use of the modeling framework under representative conditions that would be found in social network data. Advantages of the modeling framework are highlighted, and potential limitations and future directions are discussed. In recent years, psychologists and other social scientists and more intimate relationships in general, and some have become increasingly interested in analyzing network researchers argue dissolution tends to be more significant data, recognizing that social networks play a key role in for females as a result (Jalma, 2008). While dissolution is people’s lives (Borgatti, Mehra, Brass, & Labianca, 2009; an important phase of many relationships, most research Wasserman & Faust, 1994;Snijders,2005a). For exam- has focused solely on the mechanisms leading to friend- ple, attributes of adolescent peer networks are important ship formation. Schaefer, Kornienko, and Fox (2011), predictors of an individual’s substance use (Ennett et al., for example, found that depression homophily could be 2006), and socialization and social selection within net- created in a network through a withdrawal mechanism worksplayimportantrolesinshapingadolescents’reli- even in the absence of preference. However, compara- gious beliefs and behaviors (Cheadle & Schwadel, 2012). tively little research has analyzed the factors leading to Therapidriseandinfluenceofvirtualsocialnetworks friendship dissolution, and the research that has focused such as Facebook and Twitter have also highlighted the on dissolution has largely focused on romantic rela- existence of network structures and have become a focus tionships (Sprecher, 1988; Felmlee, Sprecher, & Bassin, of research as well as a vehicle for studying network 1990). A notable exception is a recent study of adoles- Downloaded by [University North Carolina - Chapel Hill] at 08:19 07 November 2017 effects for many researchers (Cha, Haddadi, Benevenuto, cent friendship dissolution that investigated whether &Gummadi,2010; Romero & Kleinberg, 2010). these relationships dissolve because of differences Friendships are naturally embedded within social between the individuals, characteristics of the friends, or networks. As time passes and circumstances or rela- both (Hartl, Laursen, & Cillessen, 2015). tionships change, friendships can dissolve—often with Although a variety of models have been developed to “considerable distress” (Baumeister & Leary, 1995,p. identify and study the basic structure of social networks, 503). Researchers have found that friendship serves many fundamental questions surrounding friendship different purposes for men and woman; from as early dissolution remain stubbornly difficult to address using as preschool to adulthood, gender differences within current analysis approaches. Example questions include friendships have been noted (Maccoby, 1990;Johnson& “What are the processes leading to a friendship ending Aries, 1983). Females have been found to develop closer and what’s the role of the individuals’ depression in this CONTACT Danielle O. Dean [email protected] Microsoft, Memorial Drive #, Cambridge, MA . Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/hmbr. © Taylor & Francis Group, LLC 272 D. O. DEAN ET AL. process?”aswellas“Howlongdoesatypicalfriendship using exponential random graph models (ERGMs), com- last?” and “Does friendship duration differ between girls monly referred to as p∗ models (Wasserman & Robins, and boys accounting for other factors?” The aim of these 2005;Frank&Strauss,1986). ERGMs are built on the questions is to understand not simply friendship length, idea that social networks are stochastic and that the but also how different covariates affect dissolution, con- patternsevidentwithinagivennetworkcanbeseenasevi- trolling for other covariates. One common aspect of these dence of specific local processes, such as reciprocity, tran- questions is that they share a concern with dyadic bonds sitivity, and homophily1 (Wasserman & Pattison, 1996). within a network (e.g., specific friendships) rather than Longitudinal social network models have become a concern with the global network structure. Another is increasingly popular in recent years to understand net- that they focus on understanding the processes leading work evolution. Many of these models are based on to—as well as timing of—an event occurring between the assumption that observed networks are the result two individuals. The aim of this article is to provide of a continuous-time Markov process (Snijders, 2005a). a modeling framework for addressing such questions, Longitudinal network data generally enable researchers accounting for the fact individuals are members of to better understand the dynamics leading to an observed multiple relationships within a larger social network. networkataparticularpointintimeasonecancondition In this article, extant modeling approaches for address- on the prior configuration of the network to better under- ing social network questions are first briefly introduced. stand the subsequent changes. For example, the actor- To better address the example questions, these meth- oriented model as implemented in the software program ods are then built upon in order to develop a general SIENA is a general and flexible framework that allows the modeling framework that utilizes event history analysis probabilities of relational changes to depend on the entire accounting for the special features (e.g., dependencies) network structure, with actors assumed to change their present within network data with a multiple-membership ties to optimize an objective function (Snijders, 2005a). random-effects structure. This modeling framework is SIENA has been used to study selection, dissolution, tested through a simulation study under representative and socialization processes of happiness in adoles- conditions that would be found in social network data cent friendship networks, for example (van Workum, and then demonstrated through an empirical application Scholte, Giletta, Cillessen, & Lodder, 2013). Alternatively, to high school social network data. Hanneke, Fu, and Xing (2010) build directly on cross- sectional ERGMs to model longitudinal network data withamodelreferredtoasatemporalERGM(TERGM), Friendship duration model adding an exponential family function for the transition Building upon a prior application of multilevel event his- probability of a network from one period to the next. tory analysis to social network data by de Nooy (2011), While these models provide a framework from which the “friendship duration” (FD) model is developed here to evaluate the processes leading to the network’s struc- to study the processes leading to the occurrence and tim- ture, they are not structured to understand whether and ingoffriendshipdissolutionbetweenindividualsembed- when a specific type of event occurs between
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