Social Network Analysis- Adolescent Friendships and Sorority Groups

Social network analysis is often used for examining the family dynamics and friendships. By conducting SNA to analyze social networks and their specific properties, we can get an insight into workings of social bonds, kinship, and support systems. In this blog, I discuss two journal articles that focus on analyzing social relationships with the help of social network analysis.

In an article “The Contribution of Extracurricular Activities to Adolescent Friendships: New Insights through Social Network Analysis”, researchers Schaefer et al (2011) use social network analysis to examine whether co-participating in school-based extracurricular activities supported adolescents’ school-based friendships. They use the ecological theory as a framework stating that adolescents’ friendships are nested within multiple larger settings, such as schools. They suggest that peer homophily meaning the similarities between people work as the primary factor promoting friendships. The authors state that the goal of this study is to “examine whether co-participating in a school-based extracurricular activity supported friendships among adolescents at the same school” (Schaefer et al, 2011). In this study, the researchers test four hypotheses.

1)    The friendships are more likely among activity co-participants than among adolescents who do not participate in the same activity

2)    The positive associations between co-participation and friendships is stronger in high school than middle school.

3)    The positive associations between co-participation and friendship is stronger in arts and academic activities than in sports activities.

4)    The activity co-participants are more likely become friends in the future than adolescents who do not participate in the same activity.

This study uses the data from The National Longitudinal Study of Adolescent Health (Add Health), which is a nationally representative study of 7th through 12th-grade adolescents across the United States. It includes the self-reported data from a cross-sectional sample of 67,124 participants from 108 schools and a longitudinal sample of 1550 adolescents in 2 schools. The data includes the measures of homophily (socio-demographic characteristics- age, gender, grade, and parent’s education); activity co-participation (school activities they participated in); friendship network (closest male and female friends); and their network structure.

For the analysis, the researchers used Exponential Random Graph Models (ERGMs) as it addresses the complex dependencies within friendship data in order to uncover underlying structural patterns and properties. The researchers suggest that ERGMs are also beneficial to understand the homophily in the social network. Also, the ERGMs were used to test the effects of activity co-participation, homophily, and endogenous network processes on friendship. The authors state that they analyze the data in three steps: 1) they examined whether activity co-participation predicted friendship above and beyond alternative friendship processes. 2) They investigated whether the relation between activity co-participation and friendship differed between middle and high schools and by activity type. 3) They used the longitudinal data to test whether activities led to the formation of new friendships eight months later.

The findings of this study suggest that activity settings play a key role in adolescents’ friendships by helping support existing friendships and the development of new friendships. Results also indicate that when two adolescents participated in the same activity, they were 2.3 times more likely on average to be friends that the adolescents who were not co-participants. The strength of this association was similar in extent to homophily on gender, race, GPA, and problem behavior but was stronger than homophily on SES, physical health, and depression. The authors conclude that activity co-participation promotes the concurrent and new friendships. In fact, the extracurricular activity settings are core within the school that promote that friendship and provide adolescents with space to interact and engage with others.

The second article I am discussing here is “Structure and Sentiment: Explaining Emotional Attachment to Group” by Pamela Paxton and James Moody. The article examines the relationship between network structure and emotional attachment in a Southern sorority. They investigate three factors in this study 1) individual’s emotional attachment to the group consisting of identity dimension (how strongly individual see themselves as a part of the group) and an affective dimension (how happy they are to be a part of this group). 2) The effects of centrality and subgroup membership on member’s emotional attachment. 3) The attachment to the sorority against the attachment to competing identities by considering the extent of participation in the sorority and competition from other groups. The study tests the following hypotheses,

“Solitary activities will provide the fewest benefits for attachment. Mandatory participation will increase emotional attachment more than solitary activities, but less than purely social participation. Negative, stressful, and antagonistic participation will decrease attachment.”

The study uses the data collected from a small southern college sorority “Alpha Beta Chi” (ABX). The group consisted of only female members who were all white and all belonged to upper middle class. Most members are also Protestants and all are within five years of each other in age. By utilizing Bollen and Hoyle’s Perceived Cohesion Scale (PCS), the researchers analyze the participant’s emotional attachment to the group. The picture below shows the specifics of PCS model.

To understand the network embeddedness of the group, the study uses centrality measures to analyze actor’s centrality and as a result of their position within a network. They also use in-degree centrality to measure the popularity of the actor. They also measure member’s degree of participation by examining the four variables 1) how many hours they spend on sorority activities, 2) how many sorority functions they attend, 3) how often they go out with other sorority members, and 4) how involved in they were in the previous year’s membership selection process. To measure the competition, the researchers included a dummy variable that indicates whether the member belongs to another group.

The results of the study indicate that network structures influence the individual’s attachment to the group. The study found an increased level of belonging and morale among central individuals, suggesting that emotional attachment corresponds to network position. They also found the highest level of emotional attachment among members of sub-groups that were internally tight-knit as well as had some cross-cutting ties to the rest of the group. The authors state that participation in group activities can lead to greater attachment, but the content of participation also affects this dynamic. All in all, the findings suggest that individuals that work for the group enjoy higher morale and participation in the organized events as well as activities increases feelings of belonging.

References,

Paxton, P., & Moody, J. (2003). Structure and Sentiment: Explaining Emotional Attachment to Group. Social Psychology Quarterly, 66(1), 34. doi:10.2307/3090139
Schaefer, D. R., Simpkins, S. D., Vest, A. E., & Price, C. D. (2011). The contribution of extracurricular activities to adolescent friendships: New insights through social network analysis. Developmental Psychology, 47(4), 1141-1152. doi:10.1037/a0024091

 

 

One thought on “Social Network Analysis- Adolescent Friendships and Sorority Groups

  1. Both of your articles are both innovative and ‘no duh’ type of conclusions. Both found that participating in groups = more emotional attachment and more friends. Durkheim would be proud of these articles. But, both also illustrate how non-SNA focused theory, i.e. cohesion and friendships, are really, at their core, network based theories. Once you are able to see that networks are everywhere as Barabasi states, you can see how almost all theory is network theory!

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