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Statistical methods have been widely employed in many practical naturallanguage processing applications. More specifically, complex networks conceptsand methods from dynamical systems theory have been successfully applied torecognize stylistic patterns in written texts. Despite the large amount ofstudies devoted to represent texts with physical models, only a few studieshave assessed the relevance of attributes derived from the analysis ofstylistic fluctuations. Because fluctuations represent a pivotal factor forcharacterizing a myriad of real systems, this study focused on the analysis ofthe properties of stylistic fluctuations in texts via topological analysis ofcomplex networks and intermittency measurements. The results showed thatdifferent authors display distinct fluctuation patterns. In particular, it wasfound that it is possible to identify the authorship of books using theintermittency of specific words. Taken together, the results described heresuggest that the patterns found in stylistic fluctuations could be used toanalyze other related complex systems. Furthermore, the discovery of novelpatterns related to textual stylistic fluctuations indicates that thesepatterns could be useful to improve the state of the art of manystylistic-based natural language processing tasks.

Authorship recognition via fluctuation analysis of network topology and word intermittency