Probing Human Response Times

TL;DR

This paper demonstrates that human response times across different communication channels and populations follow a universal power-law distribution, with significant implications for social and network dynamics.

Contribution

It shows that response time distributions are consistent across diverse datasets, supporting a generalized model of human response behavior.

Findings

Response times follow a power-law distribution ~ t^{-1}

Data from email and online news responses agree quantitatively

Implications for social and network dynamics studies

Abstract

In a recent preprint \cite{eck}, the temporal dynamics of an e-mail network has been investigated by J.P. Eckmann, E. Moses and D. Sergi. Specifically, the time period between an e-mail message and its reply were recorded. It will be shown here that their data agrees quantitatively with the frame work proposed to explain a recent experiment on the response of ``internauts'' to a news publication \cite{www2} despite differences in communication channels, topics, time-scale and socio-economic characteristics of the two population. This suggest a generalized response time distribution $\sim t^{-1}$ for human populations in the absence of deadlines with important implications for psychological and social studies as well the study of dynamical networks.