🔗 Who cites «Development and Use of a Gold-Standard Data Set for Subjectivity Classifications»

65 papers of our library cite it (of the 141,840 whose bibliographies we read) · 12 with a page here, the most cited first · ← back to «Development and Use of a Gold-Standard Data Set for Subjectivity Classifications»

Robust Sentiment Detection on Twitter from Biased and Noisy DataInternational Conference on Computational Linguistics (COLING)Luciano Barbosa, Junlan Feng2010 · 954 citations
1. Building a Discourse-Tagged Corpus in the Framework of Rhetorical Structure TheoryLynn Carlson, Daniel Marcu, Mary Ellen Okurovsky2001 · 912 citations
   Learning Subjective LanguageComputational LinguisticsJanyce Wiebe, Theresa Wilson, Rebecca Bruce, et al.2004 · 861 citations
   Recognizing Contextual Polarity: An Exploration of Features for Phrase-Level Sentiment AnalysisComputational LinguisticsTheresa Wilson, Janyce Wiebe, Paul Hoffmann2009 · 824 citations
   Effects of Adjective Orientation and Gradability on Sentence SubjectivityInternational Conference on Computational Linguistics (COLING)Vasileios Hatzivassiloglou, Janyce M. Wiebe2000 · 746 citations
   Learning subjective nouns using extraction pattern bootstrappingConference on Computational Natural Language Learning (CoNLL)Ellen Riloff, Janyce Wiebe, Theresa Wilson2003 · 580 citations
   Extracting Opinions, Opinion Holders, and Topics Expressed in Online News Media TextWorkshop on Sentiment and Subjectivity in TextSoo-Min Kim, Eduard Hovy2006 · 560 citations
   Cheap and Fast – But is it Good? Evaluating Non-Expert Annotations for Natural Language TasksConference on Empirical Methods in Natural Language Processing (EMNLP)Rion Snow, Brendan O'Connor, Daniel Jurafsky, et al.2008 · 392 citations
   Towards Answering Opinion Questions: Separating Facts from Opinions and Identifying the Polarity of Opinion SentencesConference on Empirical Methods in Natural Language Processing (EMNLP)Hong Yu, Vasileios Hatzivassiloglou2003 · 174 citations
   How Do Cultural Differences Impact the Quality of Sarcasm Annotation?: A Case Study of Indian Annotators and American TextSIGHUM Workshop on Language Technology for Cultural Heritage, Social Sciences, and HumanitiesAditya Joshi, Pushpak Bhattacharyya, Mark Carman, et al.2016 · 46 citations
2. Really? Well. Apparently Bootstrapping Improves the Performance of Sarcasm and Nastiness Classifiers for Online DialogueProceedings of the Workshop on Language Analysis in Social MediaStephanie Lukin, Marilyn Walker2013 · 31 citations
   A Corpus for Sentence-Level Subjectivity Detection on English News ArticlesLanguage Resources and Evaluation Conference (LREC)Francesco Antici, Federico Ruggeri, Andrea Galassi, et al.2024 · 10 citations

53 more papers of our library cite it; they have no page here yet.

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