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Dynamics and stability of small social networks

Dynamics and stability of small social networks
Dynamics and stability of small social networks
The choices and behaviours of individuals in social systems combine in unpredictable ways to create complex, often surprising, social outcomes. The structure of these behaviours, or interactions between individuals, can be represented as a social network. These networks are not static but vary over time as connections are made and broken or change in intensity. Generally these changes are gradual, but in some cases individuals disagree and as a result "fall out" with each other, i.e. , actively end their relationship by ceasing all contact. These "fallouts" have been shown to be capable of fragmenting the social network into disconnected parts. Fragmentation can impair the functioning of social networks and it is thus important to better understand the social processes that have such consequences.

In this thesis we investigate the question of how networks fragment: what mechanism drives the changes that ultimately result in fragmentation? To do so, we also aim to understand the necessary conditions for fragmentation to be possible and identify the connections that are most important for the cohesion of the network. To answer these questions, we need a model of social network dynamics that is stable enough such that fragmentation does not occur spontaneously, but is simultaneously dynamic enough to allow the system to react to perturbations (i.e. , disagreements). We present such a model and show that it is able to grow and maintain networks exhibiting the characteristic properties of social networks, and does so using local behavioural rules inspired by sociological theory.

We then provide a detailed investigation of fragmentation and confirm basic intuitions on the importance of bridges for network cohesion. Furthermore, we show that this topological feature alone does not explain which points of the network are most vulnerable to fragmentation. Rather, we find that dependencies between edges are crucial for understanding subtle differences between stable and vulnerable bridges. This understandingof the vulnerability of different network components is likely to be valuable for preventing fragmentation and limiting the impact of social fallout
social networks, spatial networks, networks, simulation modelling, complex systems
zu Erbach-Schoenberg, Elisabeth
9a1f59b2-c661-42c9-ad94-96772c292add
zu Erbach-Schoenberg, Elisabeth
9a1f59b2-c661-42c9-ad94-96772c292add
Brailsford, Sally
634585ff-c828-46ca-b33d-7ac017dda04f
Bullock, Seth
2ad576e4-56b8-4f31-84e0-51bd0b7a1cd3

zu Erbach-Schoenberg, Elisabeth (2014) Dynamics and stability of small social networks. University of Southampton, School of Management, Doctoral Thesis, 159pp.

Record type: Thesis (Doctoral)

Abstract

The choices and behaviours of individuals in social systems combine in unpredictable ways to create complex, often surprising, social outcomes. The structure of these behaviours, or interactions between individuals, can be represented as a social network. These networks are not static but vary over time as connections are made and broken or change in intensity. Generally these changes are gradual, but in some cases individuals disagree and as a result "fall out" with each other, i.e. , actively end their relationship by ceasing all contact. These "fallouts" have been shown to be capable of fragmenting the social network into disconnected parts. Fragmentation can impair the functioning of social networks and it is thus important to better understand the social processes that have such consequences.

In this thesis we investigate the question of how networks fragment: what mechanism drives the changes that ultimately result in fragmentation? To do so, we also aim to understand the necessary conditions for fragmentation to be possible and identify the connections that are most important for the cohesion of the network. To answer these questions, we need a model of social network dynamics that is stable enough such that fragmentation does not occur spontaneously, but is simultaneously dynamic enough to allow the system to react to perturbations (i.e. , disagreements). We present such a model and show that it is able to grow and maintain networks exhibiting the characteristic properties of social networks, and does so using local behavioural rules inspired by sociological theory.

We then provide a detailed investigation of fragmentation and confirm basic intuitions on the importance of bridges for network cohesion. Furthermore, we show that this topological feature alone does not explain which points of the network are most vulnerable to fragmentation. Rather, we find that dependencies between edges are crucial for understanding subtle differences between stable and vulnerable bridges. This understandingof the vulnerability of different network components is likely to be valuable for preventing fragmentation and limiting the impact of social fallout

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More information

Published date: 19 June 2014
Keywords: social networks, spatial networks, networks, simulation modelling, complex systems
Organisations: University of Southampton, WorldPop, Southampton Business School

Identifiers

Local EPrints ID: 365890
URI: http://eprints.soton.ac.uk/id/eprint/365890
PURE UUID: 74094728-6a7b-48f7-9952-066502a62fdb
ORCID for Sally Brailsford: ORCID iD orcid.org/0000-0002-6665-8230

Catalogue record

Date deposited: 08 Jul 2014 11:41
Last modified: 01 Dec 2018 01:36

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