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/

Zendy Plus

Presents the zaia usage as premium feature

ZAIA

Presents the pdf analysis as premium feature

PDF Analysis

Insights

Presents the summarisation as premium feature

Summarisation

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the access of premium content as premium feature

Premium Content

Zendy Tools

Zendy Open

Reports of sexual assault have been found to elicit online discourse incivility. The present study employs a computerized coding tool to examine linguistic characteristics of news media that are likely to influence discourse incivility-specifically, negative emotion, disagreement, and discussion about power relations. Additionally, machine learning was harnessed to measure the levels of comment toxicity, insult, profanity, threat, and identity attack in Reddi and Twitter posts sharing news reports of sexual assault. Findings reveal that linguistic features of news articles interact with platform community norms to predict rape culture as expressed within online responses to reports of sexual assault.

Uncivil Reactions to Sexual Assault Online: Linguistic Features of News Reports Predict Discourse Incivility