Detecting stance in tweets and analyzing its interaction with sentiment

*SEM 2016 - 5th Joint Conference on Lexical and Computational Semantics, Proceedings

Volumn , Issue , 2016, Pages 159-169

  Sobhani, Parinaz ^a   Mohammad, Saif M ^b   Kiritchenko, Svetlana ^a  

^a UNIVERSITY OF OTTAWA   (Canada)

^b NATIONAL RESEARCH COUNCIL CANADA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

DETECTION SYSTEM; SENTIMENT FEATURES;

SEMANTICS;

EID: 85021655402     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.18653/v1/s16-2021     Document Type: Conference Paper

References (36)

1. Pranav Anand, Marilyn Walker, Rob Abbott, Jean E. Fox Tree, Robeson Bowmani, and Michael Minor. 2011. Cats rule and dogs drool!: Classifying stance in online debate. In Proceedings of the Workshop on Computational Approaches to Subjectivity and Sentiment Analysis, pages 1-9.
2. Lingjia Deng and Janyce Wiebe. 2014. Sentiment propagation via implicature constraints. In Proceedings of the Conference of the European Chapter of the Association for Computational Linguistics, pages 377-385, Sweden.
3. Adam Faulkner. 2014. Automated classification of stance in student essays: An approach using stance target information and the Wikipedia link-based measure. In Proceedings of the Flairs Conference.
4. Kevin Gimpel, Nathan Schneider, Brendan O'Connor, Dipanjan Das, Daniel Mills, Jacob Eisenstein, Michael Heilman, Dani Yogatama, Jeffrey Flanigan, and Noah A. Smith. 2011. Part-of-speech tagging for Twitter: Annotation, features, and experiments. In Proceedings of the Annual Meeting of the Association for Computational Linguistics.
5. Kazi Saidul Hasan and Vincent Ng. 2013. Stance classification of ideological debates: Data, models, features, and constraints. In Proceedings of the International Joint Conference on Natural Language Processing, pages 1348-1356.
6. Minqing Hu and Bing Liu. 2004. Mining and summarizing customer reviews. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 168-177.
7. Yoshikiyo Kato, Sadao Kurohashi, Kentaro Inui, Robert Malouf, and Tony Mullen. 2008. Taking sides: User classification for informal online political discourse. Internet Research, 18(2): 177-190.
8. Svetlana Kiritchenko, Xiaodan Zhu, Colin Cherry, and Saif M. Mohammad. 2014a. NRC-Canada-2014: Detecting aspects and sentiment in customer reviews. In Proceedings of the International Workshop on Semantic Evaluation, Dublin, Ireland, August.
9. Svetlana Kiritchenko, Xiaodan Zhu, and Saif M. Mohammad. 2014b. Sentiment analysis of short informal texts. Journal of Artificial Intelligence Research, 50: 723-762.
10. Wei-Hao Lin, Theresa Wilson, Janyce Wiebe, and Alexander Hauptmann. 2006. Which side are you on Identifying perspectives at the document and sentence levels. In Proceedings of the Conference on Computational Natural Language Learning, pages 109-116.
11. Bing Liu and Lei Zhang. 2012. A survey of opinion mining and sentiment analysis. In Charu C. Aggarwal and ChengXiang Zhai, editors, Mining Text Data, pages 415-463. Springer.
12. Bing Liu. 2015. Sentiment Analysis: Mining Opinions, Sentiments, and Emotions. Cambridge University Press.
13. Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S. Corrado, and Jeff Dean. 2013. Distributed representations of words and phrases and their compositionality. In Advances in Neural Information Processing Systems, pages 3111-3119.
14. Saif M. Mohammad and Peter D. Turney. 2010. Emotions evoked by common words and phrases: Using Mechanical Turk to create an emotion lexicon. In Proceedings of the Workshop on Computational Approaches to Analysis and Generation of Emotion in Text, pages 26-34.
15. Saif M. Mohammad, Svetlana Kiritchenko, and Xiaodan Zhu. 2013. NRC-Canada: Building the stateof-the-art in sentiment analysis of tweets. In Proceedings of the International Workshop on Semantic Evaluation, Atlanta, Georgia, USA, June.
16. Saif M. Mohammad, Svetlana Kiritchenko, Parinaz Sobhani, Xiaodan Zhu, and Colin Cherry. 2016a. A dataset for detecting stance in tweets. In Proceedings of the Language Resources and Evaluation Conference, Portoroz, Slovenia.
17. Saif M. Mohammad, Svetlana Kiritchenko, Parinaz Sobhani, Xiaodan Zhu, and Colin Cherry. 2016b. SemEval-2016 Task 6: Detecting stance in tweets. In Proceedings of the International Workshop on Semantic Evaluation, San Diego, California.
18. Saif M Mohammad. 2015. Sentiment analysis: Detecting valence, emotions, and other affectual states from text.
19. Akiko Murakami and Rudy Raymond. 2010. Support or oppose Classifying positions in online debates from reply activities and opinion expressions. In Proceedings of the International Conference on Computational Linguistics, pages 869-875, Beijing, China.
20. Bo Pang and Lillian Lee. 2008. Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2(1-2): 1-135.
21. Fabian Pedregosa, Gaël Varoquaux, et al. 2011. Scikitlearn: Machine learning in Python. Journal of Machine Learning Research, 12: 2825-2830.
22. Maria Pontiki, Dimitrios Galanis, John Pavlopoulos, Harris Papageorgiou, Ion Androutsopoulos, and Suresh Manandhar. 2014. SemEval-2014 Task 4: Aspect based sentiment analysis. In Proceedings of the International Workshop on Semantic Evaluation, Dublin, Ireland, August.
23. Maria Pontiki, Dimitrios Galanis, Haris Papageogiou, Suresh Manandhar, and Ion Androutsopoulos. 2015. SemEval-2015 Task 12: Aspect based sentiment analysis. In Proceedings of the International Workshop on Semantic Evaluation, Denver, Colorado.
24. Ashwin Rajadesingan and Huan Liu. 2014. Identifying users with opposing opinions in Twitter debates. In Proceedings of the Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, pages 153-160. Washington, DC, USA.
25. Marta Recasens, Cristian Danescu-Niculescu-Mizil, and Dan Jurafsky. 2013. Linguistic models for analyzing and detecting biased language. In Proceedings of the Annual Meeting of the Association for Computational Linguistics, pages 1650-1659.
26. Sara Rosenthal, Preslav Nakov, Svetlana Kiritchenko, Saif M. Mohammad, Alan Ritter, and Veselin Stoyanov. 2015. SemEval-2015 Task 10: Sentiment analysis in Twitter. In Proceedings of the International Workshop on Semantic Evaluations.
27. Parinaz Sobhani, Diana Inkpen, and Stan Matwin. 2015. From argumentation mining to stance classification. In Proceedings of the Workshop on Argumentation Mining, pages 67-77, Denver, Colorado, USA.
28. Swapna Somasundaran and Janyce Wiebe. 2009. Recognizing stances in online debates. In Proceedings of the Annual Meeting of the Association for Computational Linguistics, pages 226-234, Suntec, Singapore.
29. Swapna Somasundaran and Janyce Wiebe. 2010. Recognizing stances in ideological on-line debates. In Proceedings of the NAACL HLT 2010 Workshop CAAGET, pages 116-124.
30. Duyu Tang, Furu Wei, Nan Yang, Ming Zhou, Ting Liu, and Bing Qin. 2014. Learning sentimentspecific word embedding for Twitter sentiment classification. In Proceedings of the Annual Meeting of the Association for Computational Linguistics, pages 1555-1565.
31. Matt Thomas, Bo Pang, and Lillian Lee. 2006. Get out the vote: Determining support or opposition from congressional floor-debate transcripts. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, pages 327-335.
32. Joseph Turian, Lev Ratinov, and Yoshua Bengio. 2010. Word representations: A simple and general method for semi-supervised learning. In Proceedings of the Annual Meeting of the Association for Computational Linguistics, pages 384-394.
33. Marilyn A. Walker, Pranav Anand, Robert Abbott, and Ricky Grant. 2012. Stance classification using dialogic properties of persuasion. In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 592-596.
34. Theresa Wilson, Janyce Wiebe, and Paul Hoffmann. 2005. Recognizing contextual polarity in phraselevel sentiment analysis. In Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing, pages 347-354, Vancouver, British Columbia, Canada.
35. Theresa Wilson, Zornitsa Kozareva, Preslav Nakov, Sara Rosenthal, Veselin Stoyanov, and Alan Ritter. 2013. SemEval-2013 Task 2: Sentiment analysis in Twitter. In Proceedings of the International Workshop on Semantic Evaluation, Atlanta, USA, June.
36. Tae Yano, Philip Resnik, and Noah A Smith. 2010. Shedding (a thousand points of) light on biased language. In Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk, pages 152-158.