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Human-centric Computing and Information Sciences

Table 11 Generalizability of our best models (XGBoost with All and BERT features) across social media platforms

From: Developing an online hate classifier for multiple social media platforms

 YouTubeRedditTwitterWikipedia
F1xgboost_all0.9110.7760.9800.861
F1xgboost_BERT0.9070.7780.9750.846
F1 in original papera0.960 [5]0.749 [73]0.900 [16]–
ROC-AUCxgboost_all0.9680.9670.9940.993
ROC-AUCxgboost_BERT0.9640.9670.9910.991
ROC-AUC in original papera–0.957 [73]–0.972 [7]
  1. We also present the results from previous research—when not reported, the cell contains (−). To facilitate reading, our results are given in italic. The results between the XGBoost (All vs BERT) in Wikipedia and Twitter platforms are significantly different with p < 0.01 (McNemar’s test). Note that the results from previous studies are not directly comparable with the current study findings
  2. aBrackets refer to sources
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