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An Automated Toxicity Classification on Social Media Using LSTM and Word Embedding
The automated identification of toxicity in texts is a crucial area in text analysis since the social media world is replete with unfiltered content that ranges from mildly abusive to downright hateful. Researchers have found an unintended bias and unfairness caused by training datasets, which cause...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Hindawi
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8863472/ https://www.ncbi.nlm.nih.gov/pubmed/35211168 http://dx.doi.org/10.1155/2022/8467349 |