Going Down the Rabbit Hole: Characterizing the Long Tail of Wikipedia Reading Sessions

TL;DR

This study quantitatively analyzes Wikipedia navigation patterns to understand 'rabbit hole' sessions, revealing how article layout, time of day, and topics influence deep exploration behaviors.

Contribution

It provides the first large-scale, data-driven characterization of Wikipedia rabbit hole sessions, linking structural, temporal, and topical factors to user navigation depth.

Findings

Article layout affects session structure.

More rabbit holes occur at night.

Readers stay within related topics during deep sessions.

Abstract

"Wiki rabbit holes" are informally defined as navigation paths followed by Wikipedia readers that lead them to long explorations, sometimes involving unexpected articles. Although wiki rabbit holes are a popular concept in Internet culture, our current understanding of their dynamics is based on anecdotal reports only. To bridge this gap, this paper provides a large-scale quantitative characterization of the navigation traces of readers who fell into a wiki rabbit hole. First, we represent user sessions as navigation trees and operationalize the concept of wiki rabbit holes based on the depth of these trees. Then, we characterize rabbit hole sessions in terms of structural patterns, time properties, and topical exploration. We find that article layout influences the structure of rabbit hole sessions and that the fraction of rabbit hole sessions is higher during the night. Moreover, readers are more likely to fall into a rabbit hole starting from articles about entertainment, sports, politics, and history. Finally, we observe that, on average, readers tend to stay focused on one topic by remaining in the semantic neighborhood of the first articles even during rabbit hole sessions. These findings contribute to our understanding of Wikipedia readers' information needs and user behavior on the Web.