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dc.contributor.authorRani, Priya
dc.contributor.authorSuryawanshi, Shardul
dc.contributor.authorGoswami, Koustava
dc.contributor.authorChakravarthi, Bharathi Raja
dc.contributor.authorFransen, Theodorus
dc.contributor.authorMcCrae, John P.
dc.date.accessioned2020-07-17T13:48:07Z
dc.date.available2020-07-17T13:48:07Z
dc.date.issued2020-05-11
dc.identifier.citationRani, Priya, Suryawanshi, Shardul, Goswami, Koustava, Chakravarthi, Bharathi Raja, Fransen, Theodorus, & McCrae, John P. (2020). A comparative study of different state-of-the-art hate speech detection methods in Hindi-English code-mixed data. Paper presented at the Language Resources and Evaluation Conference (LREC 2020) Second Workshop on Trolling, Aggression and Cyberbullying, Marseille, France, 11-16 May.en_IE
dc.identifier.urihttp://hdl.handle.net/10379/16085
dc.description.abstractHate speech detection in social media communication has become one of the primary concerns to avoid conflicts and curb undesired activities. In an environment where multilingual speakers switch among multiple languages, hate speech detection becomes a challenging task using methods that are designed for monolingual corpora. In our work, we attempt to analyze, detect and provide a comparative study of hate speech in a code-mixed social media text. We also provide a Hindi-English code-mixed data set consisting of Facebook and Twitter posts and comments. Our experiments show that deep learning models trained on this code-mixed corpus perform better.en_IE
dc.description.sponsorshipThis publication has emanated from research supported in part by a research grant from Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289 (Insight), SFI/12/RC/2289 P2 (Insight 2), & SFI/18/CRT/6223 (CRT-Centre for Research Training in Artficial Intelligence) co-funded by the European Regional Development Fund as well as by the EU H2020 programme under grant agreements 731015 (ELEXIS-European Lexical Infrastructure), 825182 (Pret- ˆ a-LLOD), and Irish Research Council ` grant IRCLA/2017/129 (CARDAMOM-Comparative Deep Models of Language for Minority and Historical Languages). The authors are grateful to Ajay Bohra and his team for sharing their data set and for their support. We would also like to thank our annotators for their contribution and lending us their precious time.en_IE
dc.formatapplication/pdfen_IE
dc.language.isoenen_IE
dc.publisherEuropean Language Resources Association (ELRA)en_IE
dc.relation.ispartofProceedings of the Second Workshop on Trolling, Aggression and Cyberbullyingen
dc.subjectHate Speechen_IE
dc.subjectCode mixingen_IE
dc.subjectConvolutional Neural Networksen_IE
dc.titleA comparative study of different state-of-the-art hate speech detection methods in Hindi-English code-mixed dataen_IE
dc.typeWorkshop paperen_IE
dc.date.updated2020-07-17T10:50:07Z
dc.local.publishedsourcehttps://www.aclweb.org/anthology/2020.trac-1.7en_IE
dc.description.peer-reviewednon-peer-reviewed
dc.contributor.funderScience Foundation Irelanden_IE
dc.contributor.funderEuropean Regional Development Funden_IE
dc.contributor.funderHorizon 2020en_IE
dc.contributor.funderIrish Research Councilen_IE
dc.internal.rssid21665191
dc.local.contactShardul Suryawanshi, Ida Business Park, Lower Dangan, Galway. Email: shardul.suryawanshi@insight-centre.org
dc.local.copyrightcheckedYes
dc.local.versionPUBLISHED
dcterms.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2289/IE/INSIGHT - Irelands Big Data and Analytics Research Centre/en_IE
dcterms.projectinfo:eu-repo/grantAgreement/EC/H2020::RIA/731015/EU/European Lexicographic Infrastructure/ELEXISen_IE
dcterms.projectinfo:eu-repo/grantAgreement/EC/H2020::RIA/825182/EU/Ready-to-use Multilingual Linked Language Data for Knowledge Services across Sectors/Pret-a-LLODen_IE
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