dc.contributor.author | Meyer, Johannes Skjeggestad | |
dc.contributor.author | Gambäck, Björn | |
dc.date.accessioned | 2019-11-13T11:56:08Z | |
dc.date.available | 2019-11-13T11:56:08Z | |
dc.date.created | 2019-11-06T16:01:57Z | |
dc.date.issued | 2019 | |
dc.identifier.isbn | 978-1-950737-43-7 | |
dc.identifier.uri | http://hdl.handle.net/11250/2628209 | |
dc.description.abstract | Hate speech detectors must be applicable across a multitude of services and platforms, and there is hence a need for detection approaches that do not depend on any information specific to a given platform. For instance, the information stored about the text’s author may differ between services, and so using such data would reduce a system’s general applicability. The paper thus focuses on using exclusively text-based input in the detection, in an optimised architecture combining Convolutional Neural Networks and Long Short-Term Memory-networks. The hate speech detector merges two strands with character n-grams and word embeddings to produce the final classification, and is shown to outperform comparable previous approaches. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Association for Computational Linguistics | nb_NO |
dc.relation.ispartof | ACL 2019 The Third Workshop on Abusive Language Online Proceedings of the Workshop | |
dc.relation.uri | https://www.aclweb.org/anthology/W19-3516/ | |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | A Platform Agnostic Dual-Strand Hate Speech Detector | nb_NO |
dc.type | Chapter | nb_NO |
dc.description.version | acceptedVersion | nb_NO |
dc.source.pagenumber | 146-156 | nb_NO |
dc.identifier.doi | 10.18653/v1/W19-3516 | |
dc.identifier.cristin | 1744670 | |
dc.description.localcode | licensed on a Creative Commons Attribution 4.0 International License. | nb_NO |
cristin.unitcode | 194,63,10,0 | |
cristin.unitname | Institutt for datateknologi og informatikk | |
cristin.ispublished | true | |
cristin.fulltext | postprint | |
cristin.qualitycode | 1 | |