Positive algorithmic bias cannot stop fragmentation in homophilic networks

Chris Blex, Taha Yasseri

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)80-97
Number of pages18
JournalJournal of Mathematical Sociology
Volume46
Issue number1
DOIs
Publication statusPublished - 2022

Keywords

  • Algorithmic bias
  • echo chambers
  • homophily
  • Schelling model
  • social networks

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