Characterizing and Detecting Hateful Users on Twitter

Understand

Most current approaches to characterize and detect hate speech focus on \textit{content} posted in Online Social Networks.

• They face shortcomings to collect and annotate hateful speech due to the incompleteness and noisiness of OSN text and the subjectivity of hate speech.
• These limitations are often aided with constraints that oversimplify the problem, such as considering only tweets containing hate-related words.
• In this work we partially address these issues by shifting the focus towards \textit{users}.