Detection of agreement vs. disagreement in meetings: training with unlabeled data
NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Mopping up: modeling wikipedia promotion decisions
Proceedings of the 2008 ACM conference on Computer supported cooperative work
Inter-coder agreement for computational linguistics
Computational Linguistics
"What i know is...": establishing credibility on Wikipedia talk pages
Proceedings of the 6th International Symposium on Wikis and Open Collaboration
Automatic detection and classification of social events
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Detecting forum authority claims in online discussions
LSM '11 Proceedings of the Workshop on Languages in Social Media
Detecting forum authority claims in online discussions
LSM '11 Proceedings of the Workshop on Languages in Social Media
Behind the article: recognizing dialog acts in Wikipedia talk pages
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
Annotation of adversarial and collegial social actions in discourse
LAW VI '12 Proceedings of the Sixth Linguistic Annotation Workshop
Identifying controversial articles in Wikipedia: a comparative study
Proceedings of the Eighth Annual International Symposium on Wikis and Open Collaboration
Deletion discussions in Wikipedia: decision factors and outcomes
Proceedings of the Eighth Annual International Symposium on Wikis and Open Collaboration
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We present the AAWD corpus, a collection of 365 discussions drawn from Wikipedia talk pages and annotated with labels capturing two kinds of social acts: alignment moves and authority claims. We describe these social acts and our annotation process, and analyze the resulting data set for interactions between participant status and social acts and between the social acts themselves.