The Growth of Longitudinal Social Network Analysis: A Review of the Key Datasets and Topics in Research on Child and Adolescent Development

Abstract

<p>The field of social network studies has expanded in recent decades. This chapter describes the design, time window, and network questions of the fifteen most-used social network datasets. These central datasets predominantly stem from American and European samples. Avenues for further social network research are discussed as well. Longitudinal social network analysis has the advantage of allowing examination of the different types of influence and complexity of social networks. It is suitable for estimating complex forms of influence that are difficult to estimate using conventional regression, such as different types of influence (e.g., convergence versus contagion or initiation versus continuation), cross-behavior processes, bundles of behaviors, and various susceptibility models. It may also incorporate the impact of social norms, multiple similarity, other actors (e.g., parents), and multiplex networks. The ongoing refinement of social network methods, their application, and critical evaluation will undoubtedly give a boost to numerous innovative studies on topics that matter for the new generation of adolescents.<br></p>