Statistical Properties of Inter-arrival Times Distribution in Social Tagging Systems

TL;DR

This paper analyzes the temporal patterns of user tagging activity in social tagging systems, revealing that correlations in user behavior influence inter-arrival times and that social interactions shape folksonomy evolution.

Contribution

It demonstrates the importance of behavioral correlations in modeling tagging activity and provides analytical insights into consensus formation in folksonomies.

Findings

Inter-arrival times are correlated with user behavior.

Social interactions influence folksonomy evolution.

Consensus on tag usage emerges among users.

Abstract

Folksonomies provide a rich source of data to study social patterns taking place on the World Wide Web. Here we study the temporal patterns of users' tagging activity. We show that the statistical properties of inter-arrival times between subsequent tagging events cannot be explained without taking into account correlation in users' behaviors. This shows that social interaction in collaborative tagging communities shapes the evolution of folksonomies. A consensus formation process involving the usage of a small number of tags for a given resources is observed through a numerical and analytical analysis of some well-known folksonomy datasets.