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IDAT@FIRE2019: Overview of the Track on Irony Detection in Arabic Tweets.

, , , , and . FIRE (Working Notes), volume 2517 of CEUR Workshop Proceedings, page 380-390. CEUR-WS.org, (2019)

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Sentiment Analysis: Adjectives and Adverbs are Better than Adjectives Alone, , , , and . Proceedings of the International Conference on Weblogs and Social Media (ICWSM), (2007)Short paper.Towards Context-Based Subjectivity Analysis., , , and . IJCNLP, page 1180-1188. The Association for Computer Linguistics, (2011)Annotating Preferences in Chats for Strategic Games., , and . LAW@ACL, page 139-143. The Association for Computer Linguistics, (2012)How's Business Going Worldwide ? A Multilingual Annotated Corpus for Business Relation Extraction., , , , and . LREC, page 3696-3705. European Language Resources Association, (2022)Automatic Detection of Stigmatizing Uses of Psychiatric Terms on Twitter., , and . LREC, page 237-243. European Language Resources Association, (2022)SeCredISData 2018: Special Session on Sentiment, Emotion, and Credibility of Information in Social Data., , , , , and . DSAA, page 638-640. IEEE, (2018)Preference Change., , , and . J. Log. Lang. Inf., 24 (3): 267-288 (2015)The VOLEM Project : a Framework for the Construction of Advanced Multilingual Lexicons., , , , and . Language Engineering Conference, page 89. IEEE Computer Society, (2002)Topic Refinement in Multi-level Hate Speech Detection., , , and . ECIR (2), volume 13981 of Lecture Notes in Computer Science, page 367-376. Springer, (2023)An Algerian Corpus and an Annotation Platform for Opinion and Emotion Analysis., , and . LREC, page 1202-1210. European Language Resources Association, (2020)