HateCircle and Unsupervised Hate Speech Detection incorporating Emotion and Contextual Semantic (ACM Journals)

“The novel HateCircle method is proposed to detect hate orientation for each term by co-occurrence patterns of words, contextual semantics, and emotion analysis. The efficient multiclass hate tweet classification algorithm is proposed with parts of speech tagging, Euclidean distance, and the Geometric median methods. Detection of hate content is more efficient in the native script compared to the Roman script, so the transliteration algorithm is also proposed for code-switch data preparation.”

https://dl.acm.org/doi/10.1145/3576913