TY - GEN
T1 - Characterizing stylistic elements in syntactic structure
AU - Feng, Song
AU - Banerjee, Ritwik
AU - Choi, Yejin
PY - 2012
Y1 - 2012
N2 - Much of the writing styles recognized in rhetorical and composition theories involve deep syntactic elements. However, most previous research for computational sty-lometric 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 inter-pretable characterization of stylistic elements. We present analytic insights with respect to the authorship attribution task in two different domains.
AB - Much of the writing styles recognized in rhetorical and composition theories involve deep syntactic elements. However, most previous research for computational sty-lometric 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 inter-pretable characterization of stylistic elements. We present analytic insights with respect to the authorship attribution task in two different domains.
UR - https://www.scopus.com/pages/publications/84883441689
M3 - Conference contribution
AN - SCOPUS:84883441689
SN - 9781937284435
T3 - EMNLP-CoNLL 2012 - 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, Proceedings of the Conference
SP - 1522
EP - 1533
BT - EMNLP-CoNLL 2012 - 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, Proceedings of the Conference
T2 - 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, EMNLP-CoNLL 2012
Y2 - 12 July 2012 through 14 July 2012
ER -