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SemEval-2015 Task 10: Sentiment Analysis in Twitter.

, , , , , and . SemEval@NAACL-HLT, page 451-463. The Association for Computer Linguistics, (2015)

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SemEval-2015 Task 10: Sentiment Analysis in Twitter., , , , , and . SemEval@NAACL-HLT, page 451-463. The Association for Computer Linguistics, (2015)Columbia NLP: Sentiment Detection of Sentences and Subjective Phrases in Social Media., , and . SemEval@COLING, page 198-202. The Association for Computer Linguistics, (2014)Columbia NLP: Sentiment Detection of Subjective Phrases in Social Media., and . SemEval@NAACL-HLT, page 478-482. The Association for Computer Linguistics, (2013)Detecting influencers in social media discussions.. ACM Crossroads, 21 (1): 40-45 (2014)SemEval-2017 Task 4: Sentiment Analysis in Twitter., , and . CoRR, (2019)Columbia NLP: Sentiment Slot Filling., , and . TAC, NIST, (2013)Towards Semi-Automated Annotation for Prepositional Phrase Attachment., , , , and . LREC, European Language Resources Association, (2010)SemEval-2014 Task 9: Sentiment Analysis in Twitter., , , and . SemEval@COLING, page 73-80. The Association for Computer Linguistics, (2014)Predicting the Type and Target of Offensive Posts in Social Media., , , , , and . NAACL-HLT (1), page 1415-1420. Association for Computational Linguistics, (2019)I Couldn't Agree More: The Role of Conversational Structure in Agreement and Disagreement Detection in Online Discussions., and . SIGDIAL Conference, page 168-177. The Association for Computer Linguistics, (2015)