English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The World Wide Web (WWW) has fundamentally changed the ways billions ofpeople are able to access information. Thus, understanding how people seekinformation online is an important issue of study. Wikipedia is a hugelyimportant part of information provision on the web, with hundreds of millionsof users browsing and contributing to its network of knowledge. The study ofnavigational behaviour on Wikipedia, due to the site's popularity and breadthof content, can reveal more general information seeking patterns that may beapplied beyond Wikipedia and the Web. Our work addresses the relativeshortcomings of existing literature in relating how information structureinfluences patterns of navigation online. We study aggregated clickstream datafor articles on the English Wikipedia in the form of a weighted, directednavigational network. We introduce two parameters that describe how articlesact to source and spread traffic through the network, based on their in/outstrength and entropy. From these, we construct a navigational phase space wheredifferent article types occupy different, distinct regions, indicating how thestructure of information online has differential effects on patterns ofnavigation. Finally, we go on to suggest applications for this analysis inidentifying and correcting deficiencies in the Wikipedia page network that mayalso be adapted to more general information networks.

Inspiration, Captivation, and Misdirection: Emergent Properties in Networks of Online Navigation