Root / Conference Proceedings / 8th International Conference on Physics and Control (PhysCon 2017) / Spectral Analysis Applications to the Literary Texts Study

Spectral Analysis Applications to the Literary Texts Study

Oleg Granichin, Natalia Kizhaeva, Zeev Volkovich

This paper presents an approach for dynamic modeling of writing process. A text is divided into sequence of sub-texts that are described through occurrences of character $N$-grams. The Mean Dependence similarity measures the association between a present sub-text and a number of preceding ones and transforms a text into a time series, which is supposed to be weak stationary if the text is created using single writing style. A periodogram of this signal estimates its Power Spectral Density providing a spectral attribute of the style. Numerical experiments demonstrate high ability of the proposed method in authorship identification and the revealing of writing style evolution.

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