Inductive learning algorithms and representations for text categorization
Proceedings of the seventh international conference on Information and knowledge management
Making large-scale support vector machine learning practical
Advances in kernel methods
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Incorporating non-local information into information extraction systems by Gibbs sampling
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
BNS feature scaling: an improved representation over tf-idf for svm text classification
Proceedings of the 17th ACM conference on Information and knowledge management
Semi-supervised recognition of sarcastic sentences in Twitter and Amazon
CoNLL '10 Proceedings of the Fourteenth Conference on Computational Natural Language Learning
Automatic acquisition of lexical formality
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Collective classification of congressional floor-debate transcripts
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Mining subjective knowledge from customer reviews: a specific case of irony detection
WASSA '11 Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis
From humor recognition to irony detection: The figurative language of social media
Data & Knowledge Engineering
Making objective decisions from subjective data: Detecting irony in customer reviews
Decision Support Systems
A multidimensional approach for detecting irony in Twitter
Language Resources and Evaluation
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We introduce the novel task of determining whether a newswire article is "true" or satirical. We experiment with SVMs, feature scaling, and a number of lexical and semantic feature types, and achieve promising results over the task.