Human dynamics revealed through Web analytics

TL;DR

This paper analyzes anonymized web access logs from Emory University to uncover human behavioral patterns, revealing that user navigation dynamics are driven by preferential linking and priority queuing.

Contribution

It introduces a systematic analysis of university web traffic, demonstrating the importance of preferential linking and queuing in understanding user navigation behavior.

Findings

User activity patterns show structured dynamics.

Preferential linking influences navigation choices.

Priority queuing explains traffic flow patterns.

Abstract

When the World Wide Web was first conceived as a way to facilitate the sharing of scientific information at the CERN (European Center for Nuclear Research) few could have imagined the role it would come to play in the following decades. Since then, the increasing ubiquity of Internet access and the frequency with which people interact with it raise the possibility of using the Web to better observe, understand, and monitor several aspects of human social behavior. Web sites with large numbers of frequently returning users are ideal for this task. If these sites belong to companies or universities, their usage patterns can furnish information about the working habits of entire populations. In this work, we analyze the properly anonymized logs detailing the access history to Emory University's Web site. Emory is a medium size university located in Atlanta, Georgia. We find interesting structure in the activity patterns of the domain and study in a systematic way the main forces behind the dynamics of the traffic. In particular, we show that both linear preferential linking and priority based queuing are essential ingredients to understand the way users navigate the Web.