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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This research draws upon cognitive psychology and information systems studiesto anticipate user engagement and decision-making on digital platforms. Byemploying natural language processing (NLP) techniques and insights fromcognitive bias research, we delve into user interactions with synonyms withindigital content. Our methodology synthesizes four cognitivebiasesRepresentativeness, Ease-of-use, Affect, and Distributioninto the READmodel. Through a comprehensive user survey, we assess the model's ability topredict user engagement, discovering that synonyms that accurately representcore ideas, are easy to understand, elicit emotional responses, and arecommonly encountered, promote greater user engagement. Crucially, our workoffers a fresh lens on human-computer interaction, digital behaviors, anddecision-making processes. Our results highlight the promise of cognitivebiases as potent indicators of user engagement, underscoring their significancein designing effective digital content across fields like education andmarketing.

Words That Stick: Predicting Decision Making and Synonym Engagement Using Cognitive Biases and Computational Linguistics