Abstract | ||
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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. |
Year | Venue | Keywords |
---|---|---|
2012 | EMNLP-CoNLL | pcfg model,deep syntactic element,composition theory,authorship attribution task,syntactic structure,writing style,salient stylistic element,stylistic element,syntactic element,analytic insight,syntactic style |
Field | DocType | Volume |
Computer science,Writing style,Rhetorical question,Attribution,Natural language processing,Artificial intelligence,Linguistics,Syntax,Sentence,Syntactic structure,Salient | Conference | D12-1 |
Citations | PageRank | References |
11 | 0.62 | 23 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Song Feng | 1 | 280 | 19.55 |
Ritwik Banerjee | 2 | 119 | 6.14 |
Yejin Choi | 3 | 2239 | 153.18 |