Hypergraph topological quantities for tagged social networks

TL;DR

This paper extends a hypergraph model for folksonomies by defining new topological measures and empirically analyzing real-world social tagging networks, revealing similarities with other complex networks.

Contribution

It introduces additional topological quantities for hypergraph models of folksonomies and demonstrates their applicability through empirical analysis of real social tagging data.

Findings

Flickr and CiteULike share similar topological features.

Tagged social networks exhibit properties common to complex networks.

Proposed measures can serve as standard tools for analyzing tagged networks.

Abstract

Recent years have witnessed the emergence of a new class of social networks, that require us to move beyond previously employed representations of complex graph structures. A notable example is that of the folksonomy, an online process where users collaboratively employ tags to resources to impart structure to an otherwise undifferentiated database. In a recent paper[1] we proposed a mathematical model that represents these structures as tripartite hypergraphs and defined basic topological quantities of interest. In this paper we extend our model by defining additional quantities such as edge distributions, vertex similarity and correlations as well as clustering. We then empirically measure these quantities on two real life folksonomies, the popular online photo sharing site Flickr and the bookmarking site CiteULike. We find that these systems share similar qualitative features with the majority of complex networks that have been previously studied. We propose that the quantities and methodology described here can be used as a standard tool in measuring the structure of tagged networks.