Repository logo
  • Log In
    New user? Click here to register.Have you forgotten your password?
University College Dublin
    Colleges & Schools
    Statistics
    All of DSpace
  • Log In
    New user? Click here to register.Have you forgotten your password?
  1. Home
  2. College of Social Sciences and Law
  3. School of Sociology
  4. Sociology Research Collection
  5. Positive algorithmic bias cannot stop fragmentation in homophilic networks
 
  • Details
Options

Positive algorithmic bias cannot stop fragmentation in homophilic networks

Author(s)
Blex, Chris  
Yasseri, Taha  
Uri
http://hdl.handle.net/10197/12719
Date Issued
2022
Date Available
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.
Other Sponsorship
Engineering and Physical Sciences Research Council
Type of Material
Journal Article
Publisher
Taylor & Francis
Journal
Journal of Mathematical Sociology
Volume
46
Issue
1
Start Page
80
End Page
97
Copyright (Published Version)
2020 the Authors
Subjects

Algorithmic bias

Echo chambers

Homophily

Schelling model

Social networks

Schelling segregratio...

Model

Emergence

Feather

Online

Media

Birds

News

DOI
10.1080/0022250X.2020.1818078
Language
English
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/
File(s)
No Thumbnail Available
Name

2001.02878.pdf

Size

276.3 KB

Format

Adobe PDF

Checksum (MD5)

91fe523aa05fedac8685a2e422ed6e5b

Owning collection
Sociology Research Collection
Mapped collections
Geary Institute Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

For all queries please contact research.repository@ucd.ie.

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Cookie settings
  • Privacy policy
  • End User Agreement