TY - JOUR
T1 - Reciprocity, transitivity, and skew
T2 - Comparing local structure in 40 positive and negative social networks
AU - McMillan, Cassie
AU - Felmlee, Diane
AU - Ashford, James R.
N1 - Funding Information:
We are grateful for feedback on previous drafts of this paper from Dave Braines, Roger Whitaker, and Chris Julien.
Publisher Copyright:
Copyright: © 2022 McMillan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2022/5
Y1 - 2022/5
N2 - While most social network research focuses on positive relational ties, such as friendship and information exchange, scholars are beginning to examine the dark side of human interaction, where negative connections represent different forms of interpersonal conflict, intolerance, and abuse. Despite this recent work, the extent to which positive and negative social network structure differs remains unclear. The current project considers whether a network’s small-scale, structural patterns of reciprocity, transitivity, and skew, or its “structural signature,” can distinguish positive versus negative links. Using exponential random graph models (ERGMs), we examine these differences across a sample of twenty distinct, negative networks and generate comparisons with a related set of twenty positive graphs. Relational ties represent multiple types of interaction such as like versus dislike in groups of adults, friendship versus cyberaggression among adolescents, and agreements versus disputes in online interaction. We find that both positive and negative networks contain more reciprocated dyads than expected by random chance. At the same time, patterns of transitivity define positive but not negative graphs, and negative networks tend to exhibit heavily skewed degree distributions. Given the unique structural signatures of many negative graphs, our results highlight the need for further theoretical and empirical research on the patterns of harmful interaction.
AB - While most social network research focuses on positive relational ties, such as friendship and information exchange, scholars are beginning to examine the dark side of human interaction, where negative connections represent different forms of interpersonal conflict, intolerance, and abuse. Despite this recent work, the extent to which positive and negative social network structure differs remains unclear. The current project considers whether a network’s small-scale, structural patterns of reciprocity, transitivity, and skew, or its “structural signature,” can distinguish positive versus negative links. Using exponential random graph models (ERGMs), we examine these differences across a sample of twenty distinct, negative networks and generate comparisons with a related set of twenty positive graphs. Relational ties represent multiple types of interaction such as like versus dislike in groups of adults, friendship versus cyberaggression among adolescents, and agreements versus disputes in online interaction. We find that both positive and negative networks contain more reciprocated dyads than expected by random chance. At the same time, patterns of transitivity define positive but not negative graphs, and negative networks tend to exhibit heavily skewed degree distributions. Given the unique structural signatures of many negative graphs, our results highlight the need for further theoretical and empirical research on the patterns of harmful interaction.
UR - http://www.scopus.com/inward/record.url?scp=85130470718&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85130470718&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0267886
DO - 10.1371/journal.pone.0267886
M3 - Article
C2 - 35594268
AN - SCOPUS:85130470718
SN - 1932-6203
VL - 17
JO - PloS one
JF - PloS one
IS - 5 May
M1 - e0267886
ER -