Interval Signature: Persistence and Distinctiveness of Inter-event Time Distributions in Online Human Behavior Jiwan Jeong Sue Moon School of Computing School of Computing KAIST KAIST
[email protected] [email protected] ABSTRACT all individuals in order to explicate or model the human be- Interval patterns, or inter-event time distributions that oc- havior [3, 13, 17, 25, 26, 36, 41]. On the contrary, we take cur in human activity, have long been an interest of many another angle and examine the diversity in individual distri- researchers studying human dynamics. While previous stud- butions of inter-event times, which we call interval pattern in ies have mostly focused on characterizing the aggregated this work. How does an individual’s interval pattern change inter-arrival patterns or finding universal patterns across all over time? Does it remain consistent or fluctuate from time individuals, we focus on the diversity among the patterns of to time? If the pattern is persistent, is it distinctive enough di↵erent individuals; the goal of this paper is to understand to characterize one from the others? how persistent an individual’s interval pattern is and how In this work we use four online datasets—Wikipedia edit distinctive it is from those of the others. We use Wikipedia, history, me2DAY, Twitter, and Enron email—to study the me2DAY, Twitter, and Enron email data to study the inter- interval patterns of users across di↵erent platforms. In par- val patterns of online human behavior. Our analysis reveals ticular, we have the entire history of Wikipedia and me2DAY, that individuals have robust and unique interval signatures.