Individual-driven versus interaction-driven burstiness in human dynamics: The case of Wikipedia edit history

TL;DR

This study investigates whether bursty editing patterns on Wikipedia are primarily driven by individual editors or by interactions among editors, revealing that weaker temporal correlations favor individual-driven burstiness.

Contribution

The paper introduces a novel measure called the degree of initiative (DoI) to quantify the dominance of individual or interaction-driven burstiness in human editing behavior.

Findings

Weaker temporal correlations correlate with higher individual-driven burstiness.

Empirical results are supported by an analytical model of edit sequences.

The approach offers deeper insights into the mechanisms behind bursty human social dynamics.

Abstract

The origin of non-Poissonian or bursty temporal patterns observed in various datasets for human social dynamics has been extensively studied, yet its understanding still remains incomplete. Considering the fact that humans are social beings, a fundamental question arises: Is the bursty human dynamics dominated by individual characteristics or by interaction between individuals? In this paper we address this question by analyzing the Wikipedia edit history to see how spontaneous individual editors are in initiating bursty periods of editing, i.e., individual-driven burstiness, and to what extent such editors' behaviors are driven by interaction with other editors in those periods, i.e., interaction-driven burstiness. We quantify the degree of initiative (DoI) of an editor of interest in each Wikipedia article by using the statistics of bursty periods containing the editor's edits. The integrated value of the DoI over all relevant timescales reveals which is dominant between individual-driven and interaction-driven burstiness. We empirically find that this value tends to be larger for weaker temporal correlations in the editor's editing behavior and/or stronger editorial correlations. These empirical findings are successfully confirmed by deriving an analytic form of the DoI from a model capturing the essential features of the edit sequence. Thus our approach provides a deeper insight into the origin and underlying mechanisms of bursts in human social dynamics.