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Comparative Study of Machine Learning Models for the Detection of Abusive Messages: Case of Wolof-French Codes Mixing Data

dc.rights.licenseopenen_US
dc.contributor.authorNDAO, I.
dc.contributor.authorDRAMÉ, K.
dc.contributor.authorSAMBE, G.
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorDIALLO, Gayo
ORCID: 0000-0002-9799-9484
IDREF: 112800084
dc.date.accessioned2025-07-11T08:34:07Z
dc.date.available2025-07-11T08:34:07Z
dc.date.issued2025-04-21
dc.date.conference2024-07-03
dc.identifier.isbn978-3-031-86493-3en_US
dc.identifier.issn1867-8211en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/207313
dc.description.abstractEnThis paper presents a comparative study of machine learning models for detecting abusive messages, focusing on code-mixed data in Wolof and French languages. With the increasing use of digital platforms, there has been a surge in derogatory comments, necessitating effective detection strategies. The study introduces a meticulously annotated dataset of 2022 Twitter tweets, manually classified as abusive or not. Extensive experiments are conducted with various machine learning algorithms, including deep learning, with a focus on comparing their performance on the test dataset. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2025.
dc.language.isoENen_US
dc.title.enComparative Study of Machine Learning Models for the Detection of Abusive Messages: Case of Wolof-French Codes Mixing Data
dc.typeCommunication dans un congrèsen_US
dc.identifier.doi10.1007/978-3-031-86493-3_20en_US
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
bordeaux.page252-263en_US
bordeaux.volume610en_US
bordeaux.hal.laboratoriesBordeaux Population Health Research Center (BPH) - UMR 1219en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionINSERMen_US
bordeaux.conference.titleEAI INTERSOL 2024 - 7th EAI International Conference on Innovations and Interdisciplinary Solutions for Underserved Areasen_US
bordeaux.countrysnen_US
bordeaux.title.proceedingInnovations and Interdisciplinary Solutions for Underserved Areas. 7th International Conference, InterSol 2024, Dakar, Senegal, July 3–4, 2024, Proceedingsen_US
bordeaux.teamAHEAD_BPHen_US
bordeaux.conference.cityDakaren_US
hal.identifierhal-05157712
hal.version1
hal.date.transferred2025-07-11T08:34:10Z
hal.proceedingsouien_US
hal.conference.end2024-07-04
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exporttrue
dc.rights.ccPas de Licence CCen_US
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.date=2025-04-21&rft.volume=610&rft.spage=252-263&rft.epage=252-263&rft.eissn=1867-8211&rft.issn=1867-8211&rft.au=NDAO,%20I.&DRAM%C3%89,%20K.&SAMBE,%20G.&DIALLO,%20Gayo&rft.isbn=978-3-031-86493-3&rft.genre=unknown


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