1. ZHAW digitalcollection
  2. School of Engineering
  3. Publikationen
  4. Publikationen School of Engineering
Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-3780
Full metadata record
DC FieldValueLanguage
dc.contributor.authorJaggi, Martin-
dc.contributor.authorUzdilli, Fatih-
dc.contributor.authorCieliebak, Mark-
dc.date.accessioned2018-06-26T14:44:03Z-
dc.date.available2018-06-26T14:44:03Z-
dc.date.issued2014-
dc.identifier.isbn978-1-63266-621-5de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/7366-
dc.description.abstractWe describe a classifier to predict the message-level sentiment of English microblog messages from Twitter. This paper describes the classifier submitted to the SemEval-2014 competition (Task 9B). Our approach was to build up on the system of the last year’s winning approach by NRC Canada 2013 (Mohammad et al., 2013), with some modifications and additions of features, and additional sentiment lexicons. Furthermore, we used a sparse (l1-regularized) SVM, instead of the more commonly used l2-regularization, resulting in a very sparse linear classifier.de_CH
dc.language.isoende_CH
dc.publisherAssociation for Computational Linguisticsde_CH
dc.rightshttp://creativecommons.org/licenses/by/4.0/de_CH
dc.subjectSupport vector machinede_CH
dc.subjectClassifierde_CH
dc.subjectSentiment analysisde_CH
dc.subject.ddc410.285: Computerlinguistikde_CH
dc.titleSwiss-chocolate : sentiment detection using sparse SVMs and part-of-speech n-gramsde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Informatik (InIT)de_CH
dc.identifier.doi10.21256/zhaw-3780-
zhaw.conference.detailsInternational Workshop on Semantic Evaluation (SemEval-2014), Dublin, Irland, 23-24 August 2014de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end604de_CH
zhaw.pages.start601de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewNot specifiedde_CH
zhaw.title.proceedingsProceedings of the International Workshop on Semantic Evaluation (SemEval-2014)de_CH
zhaw.webfeedSoftware Systemsde_CH
zhaw.webfeedNatural Language Processingde_CH
Appears in collections:Publikationen School of Engineering

Files in This Item:
File Description SizeFormat 
SemEval105.pdf119.07 kBAdobe PDFThumbnail
View/Open
Show simple item record
Jaggi, M., Uzdilli, F., & Cieliebak, M. (2014). Swiss-chocolate : sentiment detection using sparse SVMs and part-of-speech n-grams [Conference paper]. Proceedings of the International Workshop on Semantic Evaluation (SemEval-2014), 601–604. https://doi.org/10.21256/zhaw-3780
Jaggi, M., Uzdilli, F. and Cieliebak, M. (2014) ‘Swiss-chocolate : sentiment detection using sparse SVMs and part-of-speech n-grams’, in Proceedings of the International Workshop on Semantic Evaluation (SemEval-2014). Association for Computational Linguistics, pp. 601–604. Available at: https://doi.org/10.21256/zhaw-3780.
M. Jaggi, F. Uzdilli, and M. Cieliebak, “Swiss-chocolate : sentiment detection using sparse SVMs and part-of-speech n-grams,” in Proceedings of the International Workshop on Semantic Evaluation (SemEval-2014), 2014, pp. 601–604. doi: 10.21256/zhaw-3780.
JAGGI, Martin, Fatih UZDILLI und Mark CIELIEBAK, 2014. Swiss-chocolate : sentiment detection using sparse SVMs and part-of-speech n-grams. In: Proceedings of the International Workshop on Semantic Evaluation (SemEval-2014). Conference paper. Association for Computational Linguistics. 2014. S. 601–604. ISBN 978-1-63266-621-5
Jaggi, Martin, Fatih Uzdilli, and Mark Cieliebak. 2014. “Swiss-Chocolate : Sentiment Detection Using Sparse SVMs and Part-of-Speech N-Grams.” Conference paper. In Proceedings of the International Workshop on Semantic Evaluation (SemEval-2014), 601–4. Association for Computational Linguistics. https://doi.org/10.21256/zhaw-3780.
Jaggi, Martin, et al. “Swiss-Chocolate : Sentiment Detection Using Sparse SVMs and Part-of-Speech N-Grams.” Proceedings of the International Workshop on Semantic Evaluation (SemEval-2014), Association for Computational Linguistics, 2014, pp. 601–4, https://doi.org/10.21256/zhaw-3780.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.