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

Like other social media websites, YouTube is not immune from the attention ofspammers. In particular, evidence can be found of attempts to attract users tomalicious third-party websites. As this type of spam is often associated withorchestrated campaigns, it has a discernible network signature, based onnetworks derived from comments posted by users to videos. In this paper, weexamine examples of different YouTube spam campaigns of this nature, and use afeature selection process to identify network motifs that are characteristic ofthe corresponding campaign strategies. We demonstrate how these discriminatingmotifs can be used as part of a network motif profiling process that tracks theactivity of spam user accounts over time, enabling the process to scale tolarger networks.

Identifying Discriminating Network Motifs in YouTube Spam