Controlling Segregation in Social Network Dynamics as an Edge Formation Game

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

1 Scopus Citations
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Author(s)

  • Rui Luo
  • Buddhika Nettasinghe
  • Vikram Krishnamurthy

Detail(s)

Original languageEnglish
Pages (from-to)2317-2329
Number of pages13
Journal / PublicationIEEE Transactions on Network Science and Engineering
Volume9
Issue number4
Online published28 Mar 2022
Publication statusPublished - Jul 2022
Externally publishedYes

Abstract

This paper studies controlling segregation in social networks via exogenous incentives. We construct an edge formation game on a directed graph. A user (node) chooses the probability with which it forms an inter- or intra- community edge based on a utility function that reflects the tradeoff between homophily (preference to connect with individuals that belong to the same group) and the preference to obtain an exogenous incentive. Decisions made by the users to connect with each other determine the evolution of the social network. We explore an algorithmic recommendation mechanism where the exogenous incentive in the utility function is based on weak ties which incentivizes users to connect across communities and mitigates the segregation. This setting leads to a submodular game with a unique Nash equilibrium. In numerical simulations, we explore how the proposed model can be useful in controlling segregation and echo chambers in social networks under various settings. © 2022 IEEE.

Research Area(s)

  • directed stochastic block model, mechanism design, network formation game, Segregation, weak ties

Citation Format(s)

Controlling Segregation in Social Network Dynamics as an Edge Formation Game. / Luo, Rui; Nettasinghe, Buddhika; Krishnamurthy, Vikram.
In: IEEE Transactions on Network Science and Engineering, Vol. 9, No. 4, 07.2022, p. 2317-2329.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review