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

We here focus on the problem of predicting the popularity trend of usergenerated content (UGC) as early as possible. Taking YouTube videos as casestudy, we propose a novel two-step learning approach that: (1) extractspopularity trends from previously uploaded objects, and (2) predicts trends fornew content. Unlike previous work, our solution explicitly addresses theinherent tradeoff between prediction accuracy and remaining interest in thecontent after prediction, solving it on a per-object basis. Our experimentalresults show great improvements of our solution over alternatives, and itsapplicability to improve the accuracy of state-of-the-art popularity predictionmethods.

TrendLearner: Early Prediction of Popularity Trends of User Generated Content