Model of Wikipedia growth based on information exchange via reciprocal arcs

TL;DR

This paper presents a model for Wikipedia growth emphasizing reciprocal arcs, demonstrating that preferential attachment combined with reciprocal information exchange accurately reproduces real network in-degree distributions.

Contribution

The paper introduces a novel Wikipedia growth model incorporating reciprocal arcs and preferential attachment, matching real network distributions without extensive fitting.

Findings

Reciprocal arcs significantly influence Wikipedia's network structure.

The proposed model accurately reproduces real in-degree distributions.

Model parameters can be derived directly from real network measurements.

Abstract

We show how reciprocal arcs significantly influence the structural organization of Wikipedias, online encyclopedias. It is shown that random addition of reciprocal arcs in the static network cannot explain the observed reciprocity of Wikipedias. A model of Wikipedia growth based on preferential attachment and on information exchange via reciprocal arcs is presented. An excellent agreement between in-degree distributions of our model and real Wikipedia networks is achieved without fitting the distributions, but by merely extracting a small number of model parameters from the measurement of real networks.