“This report is structured in two parts: in Part 1, we introduce and discuss the concept of bias indicators, including their uses, benefits, and risks. In Part 2, we present a general list of bias indicators (which might be used to code a hate motivated incident), followed by discrete lists of bias indicators for specific target identities. We also present a separate list for online bias indicators, which might apply to one or more target identities.” https://www.crisconsortium.org/news/bias-indicators Share this: Click to print (Opens in new window) Print Click to share on Facebook (Opens in new window) Facebook Click to share on LinkedIn (Opens in new window) LinkedIn Click to share on Reddit (Opens in new window) Reddit Click to share on WhatsApp (Opens in new window) WhatsApp Click to share on Bluesky (Opens in new window) Bluesky Click to email a link to a friend (Opens in new window) Email Like this:Like Loading... Post navigation Detecting twitter hate speech in COVID-19 era using machine learning and ensemble learning techniques (International Journal of Information Management Data Insights) Using science and AI to track patterns of digital hate (Telekom)