Language and the Internet
Mining newsgroups using networks arising from social behavior
WWW '03 Proceedings of the 12th international conference on World Wide Web
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Which side are you on?: identifying perspectives at the document and sentence levels
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
More than words: syntactic packaging and implicit sentiment
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Generalizing dependency features for opinion mining
ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
Recognizing stances in online debates
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Recognizing stances in ideological on-line debates
CAAGET '10 Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
How can you say such things?!?: recognizing disagreement in informal political argument
LSM '11 Proceedings of the Workshop on Languages in Social Media
Decision Support Systems
Subgroup detection in ideological discussions
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Recognizing arguing subjectivity and argument tags
ExProM '12 Proceedings of the Workshop on Extra-Propositional Aspects of Meaning in Computational Linguistics
Online debate summarization using topic directed sentiment analysis
Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining
| Hi-index | 0.00 |
A growing body of work has highlighted the challenges of identifying the stance a speaker holds towards a particular topic, a task that involves identifying a holistic subjective disposition. We examine stance classification on a corpus of 4873 posts across 14 topics on ConvinceMe.net, ranging from the playful to the ideological. We show that ideological debates feature a greater share of rebuttal posts, and that rebuttal posts are significantly harder to classify for stance, for both humans and trained classifiers. We also demonstrate that the number of subjective expressions varies across debates, a fact correlated with the performance of systems sensitive to sentiment-bearing terms. We present results for identifing rebuttals with 63% accuracy, and for identifying stance on a per topic basis that range from 54% to 69%, as compared to unigram baselines that vary between 49% and 60%. Our results suggest that methods that take into account the dialogic context of such posts might be fruitful.