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Positive algorithmic bias cannot stop fragmentation in homophilic networks.

Authors :
Blex, Chris
Yasseri, Taha
Source :
Journal of Mathematical Sociology; 2022, Vol. 46 Issue 1, p80-97, 18p
Publication Year :
2022

Abstract

Fragmentation, echo chambers, and their amelioration in social networks have been a growing concern in the academic and non-academic world. This paper shows how, under the assumption of homophily, echo chambers and fragmentation are system-immanent phenomena of highly flexible social networks, even under ideal conditions for heterogeneity. We achieve this by finding an analytical, network-based solution to the Schelling model and by proving that weak ties do not hinder the process. Furthermore, we derive that no level of positive algorithmic bias in the form of rewiring is capable of preventing fragmentation and its effect on reducing the fragmentation speed is negligible. [ABSTRACT FROM AUTHOR]

Subjects

Subjects :
SOCIAL networks
ALGORITHMIC bias

Details

Language :
English
ISSN :
0022250X
Volume :
46
Issue :
1
Database :
Complementary Index
Journal :
Journal of Mathematical Sociology
Publication Type :
Academic Journal
Accession number :
155632811
Full Text :
https://doi.org/10.1080/0022250X.2020.1818078