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Automated identification of bias inducing words in news articles using linguistic and context-oriented features ...
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HateBERT: Retraining BERT for Abusive Language Detection in English ...
Abstract: We introduce HateBERT, a re-trained BERT model for abusive language detection in En- glish. The model was trained on RAL-E, a large-scale dataset of Reddit comments in English from communities banned for being offensive, abusive, or hateful that we have curated and made available to the public. We present the results of a detailed comparison between a general pre-trained language model and the retrained version on three English datasets for offensive, abusive language and hate speech detection tasks. In all datasets, HateBERT outperforms the corre- sponding general BERT model. We also discuss a battery of experiments comparing the portability of the fine-tuned models across the datasets, suggesting that portability is affected by compatibility of the annotated phenomena. ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://underline.io/lecture/30154-hatebert-retraining-bert-for-abusive-language-detection-in-english
https://dx.doi.org/10.48448/gvd1-fp03
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Automated identification of bias inducing words in news articles using linguistic and context-oriented features
In: Information Processing & Management ; 58 (2021), 3. - 102505. - Elsevier. - ISSN 0306-4573. - eISSN 1873-5371 (2021)
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Assessing the Quality of Web Content ...
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Facet Classification of Blogs: Know-Center at the TREC 2009 Blog Distillation Task
In: DTIC (2009)
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