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A Critical Discourse Analysis of Hate Speech Comments on Nigerian News Websites

Domain:

natural language processingpeace and security

Record type:

dataset
Creator:
Fra
Publisher:
Gal
Host:
Though hate speech has become a global phenomenon, organisations and individuals find it difficult to come up with a universal definition, or with detection techniques and classifications. This challenge has created a lacuna which has made legislation against hate speech difficult in many countries, especially Nigeria. In this study, the researcher analysed and categorised hate speech comments from two Nigerian news websites with a view to describing, categorising and identifying prevalent hate speech themes. Words with the highest frequency of occurrence in the corpus are identified. Observation and descriptive methods were used for data collection while both qualitative and quantitative approaches were adopted for analyses. The findings of the study showed that ethnic affiliation is the most common trigger of hate speech comments in Nigeria while the second person pronoun “you” used to emphasise others’ negative (EON) is the word with the highest frequency.

Visit

doi.org

Tasks

hate speech detectiontext classification

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