Drawing from my psychology background and great interest to learn more about childrens’ learning paths and experience, I focused my search for these two articles upon developmental aspects of a child’s growth, their friendships, and the use of social network analysis.
First, the work by Shin and Ryan (2014) investigated early adolescent friendship selection and social influence in relation to academic motivation, engagement, and achievement. Data was collected in classrooms using surveys at two time points, one in Fall and one in Spring, among approximately 575 (at each time point) 6th graders. Using a stochastic actor-based social network model to estimate friendship selection and influence, Shin and Ryan (2014) used students as nodes and the strength of their friendships to others as the edges or connections therein. This method, which examines changes in friendship networks and behaviors (attributes), while allowing other attributes such as gender, race, and other behaviors to be examined. Although no explicit research questions for outlined, they did offer hypotheses (which can be inferred into RQs…): They “expected that both selection and influence processes occur among friends in all aspects of academic adjustment.” and that academic self-efficacy likely serves as peer influence effects (p. 4).
Therefore, despite having very solidified research questions, they seemed to after being more descriptive than anything. That said, they found network density to decline over time, meaning adolescents dont just nominate anyone as their friend, and a positive reciprocity parameter, whereby they tend to reciprocate friendship nominations (dyad nominations). Therefore, they tended to nominate each other in friend dyads, keep the network closed, and form peer group structures in friendship networks. In terms of other attributes, they found that those with high levels of effortful behavior and GPAs were more often nominated. Interestingly, contrary to my own beliefs, those with higher values of self-efficacy tended to be nominated less. Overall, they found that “selection effects were not as pervasive as influence effects in explaining similarity among friends across the school year” (p. 8). Furthermore, students tend to select friends that are similar in GPA and confidence, while GPA is influenced by friends over time. Being friends with someone else with higher achievement tends to influence those with less initial achievement, although their confidence is not influence. Students dont seek out other that behave like them, yet tend to select those with similar GPA and similar confidence, while their behavior tends to become similar over time. Collectively, the use of SNA here allowed for a dynamic examination of how selection and particular influences mitigate friendships and what the means over time. Understanding what influences selection of friendships and how those relationships change over time is vital to understanding how students change and adjust to their surroundings over time, especially when considering their academic motivation, which is vital to continued sustainment of effort and focus.
Next, work by Parker and colleagues (2014) examined adolescences’ (N = 1,972, grade 10 among 16 schools) friendship groups to examine how hope and well-being influenced are related to such groups. The data was collected through survey methods, whereby measures of hope and well-being were collected alongside a form to fill out both male and female friends. In this case, the nodes in this SNA were the students themselves and their listed relationships were their undirected edges between students. Again, these researched did not provide explicit research questions, however, they did offer hypotheses: 1. Students from the same group of friends will resemble each other in hope and well-being, 2. Average hope in friendship groups will be associated with group well-being over and above individual level hope. To form groups of friends, they used “community detection algorithms to assign individuals to particular friendship groups. To assess if average group hope was significantly related to their subjective well-being over and above their own level of hope, they used multilevel structural equation modeling (MSEM) to both account for level effects and measurement error. 211 friendship groups were formed (~13 per school) and nodal metrics were generated that suggested a good amount of reciprocal friendships and variable centrality therein. In terms of the MSEM, they portrayed the intraclass correlations (ICC) (proportion of variance explained by the grouping effect–in this case ‘friendship group’ was the grouping variable). In that, they found that the ICC for hope was .241 and for well-being it was .293, suggesting about 25-30% of the variance was explained by their group membership, supporting hypothesis 1. Using the MSEM models, they found that individual hope was significantly related to social well-being, while average hope was not associated with emotional well-being, which was consistent with their second hypothesis. Said another way, using the contextual effect model (MSEM), demonstrated that individual subjective well-being was associated with group hope beyond individual levels of hope. Therefore, this research suggests a relationship between individual well-being and the hope of the friendship group, which implies targeting an individual hope and therefore their friendship groups hope, can be a power means to collectively increase hope and well-being. In this case, the use of SNA provided an empirical way to derive groups of students, while also providing the footing to assess a dynamic multilevel model that could pick out the particular attributes between individuals and group level variance in terms of hope and well-being.
Together, these studyies, though not exactly simple, demonstrate the utility of social network analysis to better understand how friendships matter and how other attributes can be dynamically associated therein. As we all likely know anecdotally, friendships and groups of friends can be a lifeline and provide ample means of support in difficult times. Gaining a better understanding of how these groups form, what influences them, and what they mean in terms of other attributes can provide targeting to influential interventions that can help support student success.
Parker, P. D., Ciarrochi, J., Heaven, P., Marshall, S., Sahdra, B., & Kiuru, N. (2014). Hope, friends, and subjective well-being A social network approach to peer group contextual effects. Child Development, 86(2), 642–650. https://doi.org/10.1111/cdev.12308
Shin, H., & Ryan, A. M. (2014). Early adolescent friendships and academic adjustment: Examining selection and influence processes with longitudinal social network analysis. Developmental Psychology, 50(11), 2462–2472. https://doi.org/10.1037/a0037922