Assessing the Navigational Effects of Click Biases and Link Insertion on the Web

TL;DR

This paper introduces a method to measure how click biases and link insertion can influence user navigation on websites, showing that optimal strategies depend on target pages and that topological measures can predict impact.

Contribution

It presents a novel approach for assessing the effects of click biases and link insertion on web navigation, including the use of topological proxies for impact prediction.

Findings

Optimal link modification strategies vary by target pages.

Topological measures can predict navigation impact before changes.

Simple proxies effectively estimate the effects of link modifications.

Abstract

Websites have an inherent interest in steering user navigation in order to, for example, increase sales of specific products or categories, or to guide users towards specific information. In general, website administrators can use the following two strategies to influence their visitors' navigation behavior. First, they can introduce click biases to reinforce specific links on their website by changing their visual appearance, for example, by locating them on the top of the page. Second, they can utilize link insertion to generate new paths for users to navigate over. In this paper, we present a novel approach for measuring the potential effects of these two strategies on user navigation. Our results suggest that, depending on the pages for which we want to increase user visits, optimal link modification strategies vary. Moreover, simple topological measures can be used as proxies for assessing the impact of the intended changes on the navigation of users, even before these changes are implemented.