Deep learning based fusion strategies for hate speech detection to combine the classifiers to improve classification performance (AIP Conference Procedingsw)

[T]his article demonstrates how tweets may be classified as hostile or normal based on the information they include. When the tweets had been sampled, cleaned, also separated into quantifiable parts, a few models were fabricated and analyzed. For scoring obscure information, the best-performing model was utilized, and the resultant classification accuracy was adequate. This article discusses how businesses like Twitter might employ text analytics to encourage civic duty among its users. Users may be given the option to examine and maybe alter any hostile tweets before publishing them if a the ability to tag tweets as belonging to a certain category is built into the Twitter platform at the user level.

https://pubs.aip.org/aip/acp/article/2754/1/020020/2909567/Deep-learning-based-fusion-strategies-for-hate?searchresult=1