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Analysis and classification of privacy-sensitive content in social media posts
User-generated contents often contain private information, even when they are shared publicly on social media and on the web in general. Although many filtering and natural language approaches for automatically detecting obscenities or hate speech have been proposed, determining whether a shared pos...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Springer Berlin Heidelberg
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8892403/ https://www.ncbi.nlm.nih.gov/pubmed/35261872 http://dx.doi.org/10.1140/epjds/s13688-022-00324-y |