Hate Speech Detection on Twitter: Feature Engineering v.s. Feature Selection

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Challenges for Toxic Comment Classification: An In-Depth Error Analysis (2018, methodology): “Toxic comment identification is a supervised classification task and approached by either methods including manual feature engineering (Burnap and Williams, 2015; Mehdad and Tetreault, 2016; Waseem, 2016; Davidson et al., 2017; Nobata et al., 2016; Kennedy et al., 2017; Samghabadi et al., 2017; Robi”
Challenges and frontiers in abusive content detection (2019, background): “Few publications focus specifically on the challenge of implementing abusive content detection systems at scale and in a timely manner, there are exceptions (Robinson, Zhang, & Tepper, 2018; Yao, Chelmis, & Zois, 2018).”
Hate Speech Detection: A Solved Problem? The Challenging Case of Long Tail on Twitter (2018, background): “On the one hand, most types of features are derived from words; on the other hand, our previous work already showed that the most effective features in such tasks are based on surface words [32].”