Density or Distinction? The Roles of Data Structure and Group Detection Methods in Describing Adolescent Peer Groups

UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
Kelly L. Rulison, Associate Professor (Creator)
The University of North Carolina at Greensboro (UNCG )
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Abstract: Despite cross-disciplinary interest in social influence among adolescent peer groups, significant variations in collecting and analyzing peer network data have not been explored, so it is difficult to disentangle substantive and methodological differences in peer influence studies. We analyze two types of network data (self-reported friendships and multi-informant reports of children who “hang around together a lot”) with three methods of identifying group structures (two graph theoretic approaches and principal components analysis) to explore substantive differences in results. We then link these differences back to underlying features of the networks, allowing greater insight into the general problem of identifying groups in network data. We find that different analytic approaches applied to the same network data produced moderately concordant group solutions, with higher concordances for multi-informant data. The same analytic approaches applied to different relational data (on the same nodes) produced weaker concordance, suggesting that the underlying data structure may be more salient than analytic approach in accounting for different results across studies. Behavioral similarity among group members was greatest for approaches that rest directly on density of direct ties.

Additional Information

Journal of Social Structure, 8(1)
Language: English
Date: 2007
Adolescents, Peer Groups, Network Data

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