This paper presents a new approach for offensive language and hate speech detection on social media. Our approach incorporates an offensive lexicon composed by implicit and explicit offensive and swearing expressions annotated with binary classes: context-dependent offensive and context-independent offensive. Due to the severity of the hate speech and offensive comments in Brazil  and the lack of research in Portuguese, Brazilian Portuguese is the language used to validate our method. However, the proposal may be applied to any other language or domain. Based on the obtained results, the proposed approach showed high performance results overcoming the current baselines for European and Brazilian Portuguese.
This paper presents a new approach for offensive language and hate speech detection on social media. Our approach incorporate an offensive lexicon composed by implicit and explicit offensive and swearing expressions annotated with binary classes: context-dependent and context-independent offensive. Due to the severity of the hate speech and offensive comments in Brazil , and the lack of research in Portuguese, Brazilian Portuguese is the language used to validate our method. However, the proposal may be applied to any other language or domain. Based on the obtained results, the proposed approach showed high performance results overcoming the current baselines for European and Brazilian Portuguese.
R
incorporates
incorporate
fluency
fluency fluency fluency
D
offensive
clarity
clarity clarity clarity
A
,
fluency
fluency fluency fluency