A Heterophily-Based Polarization Measure for Multi-community Networks

Sreeja Nair; Adriana Iamnitchi

doi:10.1007/978-3-031-19097-1_32

A Heterophily-Based Polarization Measure for Multi-community Networks

Sreeja Nair^*, Adriana Iamnitchi

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic

Abstract

This work proposes a heterophily-based metric for quantifying polarization in social networks where multiple ideological, antagonistic communities coexist. This metric captures node-level polarization and is built on user’s affinity towards other communities rather than their own. Node-level values can then be aggregated at the community, network, or sub-network level, providing a more detailed map of polarization. We tested our metric on the Polblogs network, White Helmets Twitter interaction network with two communities and the VoterFraud2020 domain network with five communities. We also tested our metric on dK-random graphs to verify that it results in low polarization scores, as expected. Finally, we compared our metric with two widely used polarization measures: Guerra’s polarization index and RWC.

Original language	English
Title of host publication	Proceedings of the Social Informatics - 13th International Conference 2022
Editors	Frank Hopfgartner, Kokil Jaidka, Philipp Mayr, Joemon Jose, Jan Breitsohl
Publisher	Springer
Pages	459-471
Number of pages	13
ISBN (Electronic)	978-3-031-19096-4
ISBN (Print)	9783031190964
DOIs	https://doi.org/10.1007/978-3-031-19097-1_32
Publication status	Published - 2022
Event	13th International Conference on Social Informatics - Glasgow, United Kingdom Duration: 19 Oct 2022 → 21 Oct 2022 Conference number: 13 https://www.dcs.gla.ac.uk/socinfo2022/

Publication series

Series	Lecture Notes in Computer Science
Volume	13618
ISSN	0302-9743

Conference

Conference	13th International Conference on Social Informatics
Abbreviated title	SocInfo 2022
Country/Territory	United Kingdom
City	Glasgow
Period	19/10/22 → 21/10/22
Internet address	https://www.dcs.gla.ac.uk/socinfo2022/

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10.1007/978-3-031-19097-1_32

Cite this

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title = "A Heterophily-Based Polarization Measure for Multi-community Networks",

abstract = "This work proposes a heterophily-based metric for quantifying polarization in social networks where multiple ideological, antagonistic communities coexist. This metric captures node-level polarization and is built on user{\textquoteright}s affinity towards other communities rather than their own. Node-level values can then be aggregated at the community, network, or sub-network level, providing a more detailed map of polarization. We tested our metric on the Polblogs network, White Helmets Twitter interaction network with two communities and the VoterFraud2020 domain network with five communities. We also tested our metric on dK-random graphs to verify that it results in low polarization scores, as expected. Finally, we compared our metric with two widely used polarization measures: Guerra{\textquoteright}s polarization index and RWC.",

author = "Sreeja Nair and Adriana Iamnitchi",

note = "DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.; 13th International Conference on Social Informatics, SocInfo 2022 ; Conference date: 19-10-2022 Through 21-10-2022",

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doi = "10.1007/978-3-031-19097-1_32",

language = "English",

isbn = "9783031190964",

series = "Lecture Notes in Computer Science",

publisher = "Springer",

pages = "459--471",

editor = "Frank Hopfgartner and Kokil Jaidka and Philipp Mayr and Joemon Jose and Jan Breitsohl",

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Nair, S & Iamnitchi, A 2022, A Heterophily-Based Polarization Measure for Multi-community Networks. in F Hopfgartner, K Jaidka, P Mayr, J Jose & J Breitsohl (eds), Proceedings of the Social Informatics - 13th International Conference 2022. Springer, Lecture Notes in Computer Science, vol. 13618, pp. 459-471, 13th International Conference on Social Informatics, Glasgow, United Kingdom, 19/10/22. https://doi.org/10.1007/978-3-031-19097-1_32

A Heterophily-Based Polarization Measure for Multi-community Networks. / Nair, Sreeja; Iamnitchi, Adriana.
Proceedings of the Social Informatics - 13th International Conference 2022. ed. / Frank Hopfgartner; Kokil Jaidka; Philipp Mayr; Joemon Jose; Jan Breitsohl. Springer, 2022. p. 459-471 (Lecture Notes in Computer Science, Vol. 13618).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic

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AU - Iamnitchi, Adriana

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AB - This work proposes a heterophily-based metric for quantifying polarization in social networks where multiple ideological, antagonistic communities coexist. This metric captures node-level polarization and is built on user’s affinity towards other communities rather than their own. Node-level values can then be aggregated at the community, network, or sub-network level, providing a more detailed map of polarization. We tested our metric on the Polblogs network, White Helmets Twitter interaction network with two communities and the VoterFraud2020 domain network with five communities. We also tested our metric on dK-random graphs to verify that it results in low polarization scores, as expected. Finally, we compared our metric with two widely used polarization measures: Guerra’s polarization index and RWC.

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M3 - Chapter

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EP - 471

BT - Proceedings of the Social Informatics - 13th International Conference 2022

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A2 - Jaidka, Kokil

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A2 - Breitsohl, Jan

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T2 - 13th International Conference on Social Informatics

Y2 - 19 October 2022 through 21 October 2022

ER -

A Heterophily-Based Polarization Measure for Multi-community Networks

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