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dc.contributorDepartment of Computingen_US
dc.contributorDepartment of Chinese and Bilingual Studiesen_US
dc.creatorXiang, Ren_US
dc.creatorGao, Xen_US
dc.creatorLong, Yen_US
dc.creatorLi, Aen_US
dc.creatorChersoni, Een_US
dc.creatorLu, Qen_US
dc.creatorHuang, CRen_US
dc.rights© European Language Resources Association (ELRA), licensed under CC-BY-NC
dc.rightsThe following publication Xiang, R., Gao, X., Long, Y., Li, A., Chersoni, E., Lu, Q., & Huang, C. R. (2020, May). Ciron: a New Benchmark Dataset for Chinese Irony Detection. In Proceedings of The 12th Language Resources and Evaluation Conference (pp. 5714-5720) is available at
dc.subjectIrony detectionen_US
dc.subjectChinese benchmark dataseten_US
dc.subjectSocial media texten_US
dc.subjectText processingen_US
dc.titleCiron : a new benchmark dataset for Chinese irony detectionen_US
dc.typeConference Paperen_US
dcterms.abstractAutomatic Chinese irony detection is a challenging task, and it has a strong impact on linguistic research. However, Chinese irony detection often lacks labeled benchmark datasets. In this paper, we introduce Ciron, the first Chinese benchmark dataset available for irony detection for machine learning models. Ciron includes more than 8.7K posts, collected from Weibo, a micro blogging platform. Most importantly, Ciron is collected with no pre-conditions to ensure a much wider coverage. Evaluation on seven different machine learning classifiers proves the usefulness of Ciron as an important resource for Chinese irony detection.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationProceedings of the 12th Conference on Language Resources and Evaluation, LREC, May 2020, p. 5714-5720en_US
dc.relation.ispartofbookProceedings of the 12th Language Resources and Evaluation Conferenceen_US
dc.relation.conferenceLanguage Resources and Evaluation Conferenceen_US
dc.description.validate202106 bcvcen_US
dc.description.oaVersion of Recorden_US
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