Reproducibility Report: Contextualizing Hate Speech Classifiers with Post-hoc Explanation
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Abstract (arXiv)
The presented report evaluates Contextualizing Hate Speech Classifiers with Post-hoc Explanation paper within the scope of ML Reproducibility Challenge 2020. Our work focuses on both aspects constituting the paper: the method itself and the validity of the stated results. In the following sections, we have described the paper, related works, algorithmic frameworks, our experiments and evaluations.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 17 references that are in the map. First posted on arXiv 24 May 2021.
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7 of 17 references.
References · 7
- 2019Probing Neural Network Comprehension of Natural Language Argumentscited by 214
- 2018Hate Speech Dataset from a White Supremacy Forumcited by 198
- 2020Contextualizing Hate Speech Classifiers with Post-hoc Explanationcited by 84
- 2016Analyzing the Targets of Hate in Online Social Mediacited by 49
- 2018What is Gab? A Bastion of Free Speech or an Alt-Right Echo Chamber?cited by 24
- 2018The Effect of Extremist Violence on Hateful Speech Onlinecited by 17
- 2018Inside the Right-Leaning Echo Chambers: Characterizing Gab, an Unmoderated Social Systemcited by 10
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