Asocial balance—how your friends determine your enemies: understanding the co-evolution of friendship and enmity interactions in a virtual world
Maximilian Sadilek,
Peter Klimek () and
Stefan Thurner
Additional contact information
Maximilian Sadilek: Medical University of Vienna
Journal of Computational Social Science, 2018, vol. 1, issue 1, No 14, 227-239
Abstract:
Abstract Social interactions take place simultaneously through different interaction types, such as communication, friendship, trade, exchange, enmity, revenge, etc. These interactions can be conveniently described with time-dependent multi-layer networks. Little is known about the dynamics of social network formation on single layers. How the dynamics on one layer is coupled to and influences the dynamics on another layer is a completely unexplored territory. This is mainly due to the lack of comprehensive microscopic interaction data on time-dependent multi-layer networks. In this work, we study a unique dataset of 350,000 odd players in a massive multi-player online game, for which we know practically every social interaction event. We focus on the dynamics of friendship interactions and how they are coupled to the dynamics of enmity interactions. We are able to identify the driving processes behind the joint network formation of friendship and enmity links. The essential mechanisms turn out to be specific triadic closure rules. We propose a simple dynamical model that allows us to predict not only the correct levels of social balance but also the detailed simultaneous structural properties of the friendship and enmity networks, including their degree distributions, clustering coefficients and nearest neighbor degrees. While the formation of new friendship links can be largely understood on the basis of structural features of the friendship network alone, this is not true for enmity networks. The formation of enmity links is driven by the need to socially balance triadic relations that contain negative and positive interactions. Networks of enmity relations can only be understood structurally in the context of the positive social ties they are embedded in.
Keywords: Social network formation; Triadic closure; Social balance; Co-evolution; Multi-layer network (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://link.springer.com/10.1007/s42001-017-0010-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:jcsosc:v:1:y:2018:i:1:d:10.1007_s42001-017-0010-9
Ordering information: This journal article can be ordered from
http://www.springer. ... iences/journal/42001
DOI: 10.1007/s42001-017-0010-9
Access Statistics for this article
Journal of Computational Social Science is currently edited by Takashi Kamihigashi
More articles in Journal of Computational Social Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().