Paper Info
Title
Fairness on the web: alternatives to the power law
Abstract
This paper presents several measures of fairness and inequality based on the degree distribution in networks, as alternatives to the well-established power-law exponent. Networks such as social networks, communication networks and the World Wide Web itself are often characterized by their unequal distribution of edges: Few nodes are attached to many edges, while many nodes are attached to only few edges. The inequality of such network structures is typically measured using the power-law exponent, stating that the number of nodes with a given degree is proportional to that degree taken to a certain exponent. However, this approach has several weaknesses, such as its narrow applicability and expensive computational complexity. Beyond the fact that power laws are by far not a universal phenomenon on the Web, the power-law exponent has the surprising property of being negatively correlated with the usual notion of inequality, making it unintuitive as a fairness measure. As alternatives, we propose several measures based on the Lorenz curve, which is used in economics but rarely in networks study, and on the information-theoretical concept of entropy. We show in experiments on a large collection of online networks that these measures do not suffer under the drawbacks of the power-law exponent.
Year
DOI
Venue
2012
10.1145/2380718.2380741
WebSci
Keywords
Field
DocType
fairness measure,networks study,power-law exponent,power law,degree distribution,lorenz curve,unequal distribution,well-established power-law exponent,communication network,world wide web,certain exponent,entropy,network analysis
World Wide Web,Mathematical optimization,Telecommunications network,Social network,Exponent,Lorenz curve,Computer science,Degree distribution,Fairness measure,Network analysis,Computational complexity theory
Conference
Citations 
PageRank 
References 
14
4.72
9
Authors
2
Name
Order
Citations
PageRank
Jérôme Kunegis187451.20
Julia Preusse2426.30