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 Tools annual

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 monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Getting deeper insights into the online browsing behavior of Web users hasbeen a major research topic since the advent of the WWW. It provides usefulinformation to optimize website design, Web browser design, search enginesofferings, and online advertisement. We argue that new technologies and newservices continue to have significant effects on the way how people browse theWeb. For example, listening to music clips on YouTube or to a radio station onLast.fm does not require users to sit in front of their computer. Social mediaand networking sites like Facebook or micro-blogging sites like Twitter haveattracted new types of users that previously were less inclined to go online.These changes in how people browse the Web feature new characteristics whichare not well understood so far. In this paper, we provide novel and uniqueinsights by presenting first results of DOBBS, our long-term effort to create acomprehensive and representative dataset capturing online user behavior. Wefirstly investigate the concepts of parallel browsing and passive browsing,showing that browsing the Web is no longer a dedicated task for many users.Based on these results, we then analyze their impact on the calculation of auser's dwell time -- i.e., the time the user spends on a webpage -- which hasbecome an important metric to quantify the popularity of websites.

Analysing Parallel and Passive Web Browsing Behavior and its Effects on Website Metrics