Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Mining the peanut gallery: opinion extraction and semantic classification of product reviews
WWW '03 Proceedings of the 12th international conference on World Wide Web
Feedback for guiding reflection on teamwork practices
Proceedings of the 2007 international ACM conference on Supporting group work
International Journal of Web Based Communities
Using linguistic cues for the automatic recognition of personality in conversation and text
Journal of Artificial Intelligence Research
The lie detector: explorations in the automatic recognition of deceptive language
ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
Detecting deception through linguistic analysis
ISI'03 Proceedings of the 1st NSF/NIJ conference on Intelligence and security informatics
An exploration of off topic conversation
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
WEKA---Experiences with a Java Open-Source Project
The Journal of Machine Learning Research
Finding deceptive opinion spam by any stretch of the imagination
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Experiments with SVM to classify opinions in different domains
Expert Systems with Applications: An International Journal
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The present paper addresses the question of the nature of deception language. Specifically, the main aim of this piece of research is the exploration of deceit in Spanish written communication. We have designed an automatic classifier based on Support Vector Machines (SVM) for the identification of deception in an ad hoc opinion corpus. In order to test the effectiveness of the LIWC2001 categories in Spanish, we have drawn a comparison with a Bag-of-Words (BoW) model. The results indicate that the classification of the texts is more successful by means of our initial set of variables than with the latter system. These findings are potentially applicable to areas such as forensic linguistics and opinion mining, where extensive research on languages other than English is needed.