Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Reciprocity, transitivity, and skew: comparing local structure in 40 positive and negative social networks

McMillan, Cassie, Felmlee, Diane and Ashford, James R. 2022. Reciprocity, transitivity, and skew: comparing local structure in 40 positive and negative social networks. PLoS ONE 17 (5) , e0267886. 10.1371/journal.pone.0267886

[thumbnail of pone.0267886.pdf] PDF - Published Version
Available under License Creative Commons Attribution.

Download (1MB)

Abstract

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.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Additional Information: License information from Publisher: LICENSE 1: URL: http://creativecommons.org/licenses/by/4.0/
Publisher: Public Library of Science
ISSN: 1932-6203
Date of First Compliant Deposit: 24 May 2022
Date of Acceptance: 19 April 2022
Last Modified: 24 May 2023 00:41
URI: https://orca.cardiff.ac.uk/id/eprint/150007

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics