Heterogenous scaling in interevent time of on-line bookmarking

TL;DR

This study analyzes bookmarking behaviors on Delicious.com, revealing power-law decay in interevent times with different dynamics within intra-day and inter-day ranges, influenced by user activity levels.

Contribution

The paper uncovers distinct scaling behaviors in human online bookmarking actions and introduces a temporal-preference model to explain activity-dependent variations.

Findings

Interevent time distributions decay as power laws at both individual and population levels.

A significant change in the power-law exponent occurs between intra-day and inter-day ranges.

Less active users tend to follow Poisson process-like bookmarking patterns.

Abstract

In this paper, we study the statistical properties of bookmarking behaviors in Delicious.com. We find that the interevent time distributions of bookmarking decays powerlike as interevent time increases at both individual and population level. Remarkably, we observe a significant change in the exponent when interevent time increases from intra-day to inter-day range. In addition, dependence of exponent on individual Activity is found to be different in the two ranges. These results suggests that mechanisms driving human actions are different in intra- and inter-day range. Instead of monotonically increasing with Activity, we find that inter-day exponent peaks at value around 3. We further show that less active users are more likely to resemble poisson process in bookmarking. Based on the temporal-preference model, preliminary explanations for this dependence have been given . Finally, a universal behavior in inter-day scale is observed by considering the rescaled variable.