Statistical Properties of Inter-arrival Times Distribution in Social Tagging Systems
This addresses the understanding of temporal patterns in collaborative tagging for researchers in social computing, but it is incremental as it builds on existing folksonomy studies.
The study analyzed inter-arrival times in social tagging systems and found that correlations in user behavior are necessary to explain the statistical properties, showing that social interaction shapes folksonomy evolution, with consensus formation observed through analysis of datasets.
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.