Collective dynamics of social annotation

TL;DR

This paper models social annotation systems as a collective exploration of a semantic graph using random walks, explaining vocabulary growth and complex network structures emerging from user annotations.

Contribution

It introduces a novel modeling framework that applies concepts from statistical physics and complex networks to understand social annotation dynamics.

Findings

Reproduces vocabulary growth patterns

Explains complex network structures of annotations

Models social annotation as random walks on semantic graphs

Abstract

The enormous increase of popularity and use of the WWW has led in the recent years to important changes in the ways people communicate. An interesting example of this fact is provided by the now very popular social annotation systems, through which users annotate resources (such as web pages or digital photographs) with text keywords dubbed tags. Understanding the rich emerging structures resulting from the uncoordinated actions of users calls for an interdisciplinary effort. In particular concepts borrowed from statistical physics, such as random walks, and the complex networks framework, can effectively contribute to the mathematical modeling of social annotation systems. Here we show that the process of social annotation can be seen as a collective but uncoordinated exploration of an underlying semantic space, pictured as a graph, through a series of random walks. This modeling framework reproduces several aspects, so far unexplained, of social annotation, among which the peculiar growth of the size of the vocabulary used by the community and its complex network structure that represents an externalization of semantic structures grounded in cognition and typically hard to access.