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

Hate speech is one type of harmful online content which directly attacks orpromotes hate towards a group or an individual member based on their actual orperceived aspects of identity, such as ethnicity, religion, and sexualorientation. With online hate speech on the rise, its automatic detection as anatural language processing task is gaining increasing interest. However, it isonly recently that it has been shown that existing models generalise poorly tounseen data. This survey paper attempts to summarise how generalisable existinghate speech detection models are, reason why hate speech models struggle togeneralise, sums up existing attempts at addressing the main obstacles, andthen proposes directions of future research to improve generalisation in hatespeech detection.

Towards generalisable hate speech detection: a review on obstacles and solutions