Inequality and inequity in network-based ranking and recommendation algorithms
Scientific Reports, vol. 12, pp. 2012
Abstract
Though algorithms promise many benefits including efficiency, objectivity and accuracy, they may also introduce or amplify biases. Here we study two well-known algorithms, namely PageRank and Who-to-Follow (WTF), and show to what extent their ranks produce inequality and inequity when applied to directed social networks. To this end, we propose a directed network model with preferential attachment and homophily (DPAH) and demonstrate the influence of network structure on the rank distributions of these algorithms. Our main findings suggest that (i) inequality is positively correlated with inequity, (ii) inequality is driven by the interplay between preferential attachment, homophily, node activity and edge density, and (iii) inequity is driven by the interplay between homophily and minority size. In particular, these two algorithms reduce, replicate and amplify the representation of minorities in top ranks when majorities are homophilic, neutral and heterophilic, respectively. Moreover, when this representation is reduced, minorities may improve their visibility in the rank by connecting strategically in the network. For instance, by increasing their out-degree or homophily when majorities are also homophilic. These findings shed light on the social and algorithmic mechanisms that hinder equality and equity in network-based ranking and recommendation algorithms.
Authors 4
-
Central European University · Complexity Science Hub · Universität Koblenz
Affiliation as printed
Central European University, Vienna, Austria
Complexity Science Hub, Vienna, Austria
University of Koblenz-Landau, Koblenz, Germany
-
Claudia Wagner Aachen
GESIS - Leibniz Institute for the Social Sciences · Complexity Science Hub · RWTH Aachen University
Affiliation as printed
Complexity Science Hub, Vienna, Austria
GESIS - Leibniz Institute for the Social Sciences, Cologne, Germany
RWTH Aachen University, Aachen, Germany
-
University of Mannheim · GESIS - Leibniz Institute for the Social Sciences · Complexity Science Hub
Affiliation as printed
Complexity Science Hub, Vienna, Austria
GESIS - Leibniz Institute for the Social Sciences, Cologne, Germany
University of Mannheim, Mannheim, Germany
-
Fariba Karimi corresponding
Affiliation as printed
Complexity Science Hub, Vienna, Austria. karimi@csh.ac.at
Complexity Science Hub, Vienna, Austria
Cited by 38 stored of 38
No patents citing this paper on Lens.org (checked 2026-10-06).