Positive algorithmic bias cannot stop fragmentation in homophilic networks
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|Title:||Positive algorithmic bias cannot stop fragmentation in homophilic networks||Authors:||Blex, Chris; Yasseri, Taha||Permanent link:||http://hdl.handle.net/10197/12719||Date:||13-Sep-2020||Online since:||2022-01-12T12:49:52Z||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.||Funding Details:||Engineering and Physical Sciences Research Council||Type of material:||Journal Article||Publisher:||Taylor & Francis||Journal:||Journal of Mathematical Sociology||Copyright (published version):||2020 the Authors||Keywords:||Algorithmic bias; Echo chambers; Homophily; Schelling model; Social networks; Schelling segregration; Model; Emergence; Feather; Online; Media; Birds; News||DOI:||10.1080/0022250X.2020.1818078||Language:||en||Status of Item:||Peer reviewed||ISSN:||0022-250X||This item is made available under a Creative Commons License:||https://creativecommons.org/licenses/by-nc-nd/3.0/ie/|
|Appears in Collections:||Sociology Research Collection|
Geary Institute Research Collection
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