Not logged in.

Contribution Details

Type Journal Article
Scope Discipline-based scholarship
Title Network-based ranking in social systems: three challenges
Organization Unit
Authors
  • Manuel Mariani
  • Linyuan Lü
Contributors
  • Journal of Physics: Complexity
  • 2632-072X
  • IOP Publishing
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • English
Journal Title Journal of Physics: Complexity
Publisher IOP Publishing
Geographical Reach international
ISSN 2632-072X
Volume 1
Number 1
Page Range 011001
Date 2020
Abstract Text Ranking algorithms are pervasive in our increasingly digitized societies, with important real-world applications including recommender systems, search engines, and influencer marketing practices. From a network science perspective, network-based ranking algorithms solve fundamental problems related to the identification of vital nodes for the stability and dynamics of a complex system. Despite the ubiquitous and successful applications of these algorithms, we argue that our understanding of their performance and their applications to real-world problems face three fundamental challenges: (1) rankings might be biased by various factors; (2) their effectiveness might be limited to specific problems; and (3) agents’ decisions driven by rankings might result inpotentially vicious feedback mechanisms and unhealthy systemic consequences. Methods rooted innetwork science and agent-based modeling can help us to understand and overcome these challenges.
Free access at DOI
Official URL https://iopscience.iop.org/article/10.1088/2632-072X/ab8a61/pdf
Related URLs
Digital Object Identifier 10.1088/2632-072X/ab8a61
Other Identification Number merlin-id:19510
PDF File Download from ZORA
Export BibTeX
EP3 XML (ZORA)