Anomalous popularity growth in social tagging ecosystems

TL;DR

This paper investigates the unusual fluctuations in tag popularity growth in social tagging systems, modeling the process with a stochastic approach and introducing a scaling factor to quantify deviations from expected growth patterns.

Contribution

It introduces a scaling factor to measure anomalous popularity growth deviations in social tagging ecosystems, extending the Yule--Simon process model.

Findings

Large fluctuations in tag popularity are observed beyond the predictions of the standard model.

A scaling factor effectively quantifies the degree of anomalous growth.

Possible triggers for anomalous behavior are discussed.

Abstract

In social tagging systems, the diversity of tag vocabulary and the popularity of such tags continue to increase as they are exposed to selection pressure derived from our cognitive nature and cultural preferences. This is analogous to living ecosystems, where mutation and selection play a dominant role. Such population dynamism, which yields a scaling law, is mathematically modeled by a simple stochastic process---the Yule--Simon process, which describes how new words are introduced to the system and then grow. However, in actual web services, we have observed that a large fluctuation emerges in the popularity growth of individual tags that cannot be explained by the ordinary selection mechanism. We introduce a scaling factor to quantify the degree of the deviation in the popularity growth from the mean-field solution of the Yule--Simon process, and we discuss possible triggers of such anomalous popularity behavior.