Authorship Attribution with Support Vector Machines
Applied Intelligence
Automatic text categorization in terms of genre and author
Computational Linguistics
Using syntactic dependency as local context to resolve word sense ambiguity
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Language independent authorship attribution using character level language models
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
University of Manitoba: description of the PIE system used for MUC-6
MUC6 '95 Proceedings of the 6th conference on Message understanding
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Journal of the American Society for Information Science and Technology
Stylistic text classification using functional lexical features: Research Articles
Journal of the American Society for Information Science and Technology
Searching with style: authorship attribution in classic literature
ACSC '07 Proceedings of the thirtieth Australasian conference on Computer science - Volume 62
LIBLINEAR: A Library for Large Linear Classification
The Journal of Machine Learning Research
Kernel methods, syntax and semantics for relational text categorization
Proceedings of the 17th ACM conference on Information and knowledge management
Authorship attribution and verification with many authors and limited data
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Revisiting readability: a unified framework for predicting text quality
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Reverse engineering of tree kernel feature spaces
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Authorship attribution using probabilistic context-free grammars
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
Tree topological features for unlexicalized parsing
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Gender attribution: tracing stylometric evidence beyond topic and genre
CoNLL '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning
Effective and scalable authorship attribution using function words
AIRS'05 Proceedings of the Second Asia conference on Asia Information Retrieval Technology
N-Gram feature selection for authorship identification
AIMSA'06 Proceedings of the 12th international conference on Artificial Intelligence: methodology, Systems, and Applications
Exploiting parse structures for native language identification
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
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Much of the writing styles recognized in rhetorical and composition theories involve deep syntactic elements. However, most previous research for computational stylometric analysis has relied on shallow lexico-syntactic patterns. Some very recent work has shown that PCFG models can detect distributional difference in syntactic styles, but without offering much insights into exactly what constitute salient stylistic elements in sentence structure characterizing each authorship. In this paper, we present a comprehensive exploration of syntactic elements in writing styles, with particular emphasis on interpretable characterization of stylistic elements. We present analytic insights with respect to the authorship attribution task in two different domains.