方法证据记录
Hate Speech Detection
Hate speech detection is a natural-language-processing task that automatically identifies hateful, offensive, or harmful text on social media and online platforms. The task was sharpened by Davidson and colleagues (2017), who showed why separating genuine hate speech from merely offensive language is a hard, distinct classification problem rather than a single toxicity score.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Automated Hate Speech Detection
分类方法记录 · process-pipeline / text-mining
- Davidson, T., Warmsley, D., Macy, M. & Weber, I. (2017). Automated Hate Speech Detection and the Problem of Offensive Language. ICWSM, 11(1), 512-515. · DOI 10.1609/icwsm.v11i1.14955
- Fortuna, P. & Nunes, S. (2018). A Survey on Automatic Detection of Hate Speech in Text. ACM Computing Surveys, 51(4), 1-30. · DOI 10.1145/3232676
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