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Approaches for Automatically Tagging Affect: Steps Toward an Effective and Efficient Tool.

, , and . Computing Attitude and Affect in Text, volume 20 of The Information Retrieval Series, Springer, (2006)

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Automatically Identifying Good Conversations Online (Yes, They Do Exist!)., , and . ICWSM, page 628-631. AAAI Press, (2017)Personalizing Grammatical Error Correction: Adaptation to Proficiency Level and L1., and . CoRR, (2020)Humor in Collective Discourse: Unsupervised Funniness Detection in the New Yorker Cartoon Caption Contest., , , , , , , , , and 1 other author(s). LREC, European Language Resources Association (ELRA), (2016)Building Subjectivity Lexicon(s) from Scratch for Essay Data., , , , and . CICLing (1), volume 7181 of Lecture Notes in Computer Science, page 591-602. Springer, (2012)Personalizing Grammatical Error Correction: Adaptation to Proficiency Level and L1., and . W-NUT@EMNLP, page 27-33. Association for Computational Linguistics, (2019)Using system and user performance features to improve emotion detection in spoken tutoring dialogs., , , , , and . INTERSPEECH, ISCA, (2006)Dear Sir or Madam, May I Introduce the GYAFC Dataset: Corpus, Benchmarks and Metrics for Formality Style Transfer., and . NAACL-HLT, page 129-140. Association for Computational Linguistics, (2018)BUMP: A Benchmark of Unfaithful Minimal Pairs for Meta-Evaluation of Faithfulness Metrics., , , , , , , and . ACL (1), page 12788-12812. Association for Computational Linguistics, (2023)Ground Truth for Grammaticality Correction Metrics., , , and . ACL (2), page 588-593. The Association for Computer Linguistics, (2015)Robust Systems for Preposition Error Correction Using Wikipedia Revisions., , , and . HLT-NAACL, page 507-517. The Association for Computational Linguistics, (2013)