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2012
DOI: 10.1103/physreve.86.031108
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Generalized Hurst exponent and multifractal function of original and translated texts mapped into frequency and length time series

Abstract: A nonlinear dynamics approach can be used in order to quantify complexity in written texts. As a first step, a one-dimensional system is examined : two written texts by one author (Lewis Carroll) are considered, together with one translation, into an artificial language, i.e. Esperanto are mapped into time series. Their corresponding shuffled versions are used for obtaining a "base line". Two different one-dimensional time series are used here: (i) one based on word lengths (LTS), (ii) the other on word freque… Show more

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Cited by 72 publications
(44 citation statements)
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References 69 publications
(77 reference statements)
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“…Pearson correlation coefficient |r| between F (X) (j=0) and the most informative measurements found for W = 1300 (see table 3). Because all correlations assume low values, the information conveyed by F (X) (2) differs from the simple average X = F (X) (0) .…”
Section: Stylistic Variation Among Booksmentioning
confidence: 99%
See 2 more Smart Citations
“…Pearson correlation coefficient |r| between F (X) (j=0) and the most informative measurements found for W = 1300 (see table 3). Because all correlations assume low values, the information conveyed by F (X) (2) differs from the simple average X = F (X) (0) .…”
Section: Stylistic Variation Among Booksmentioning
confidence: 99%
“…To construct the tree, the C4.5 algorithm was employed in subtexts comprising W = 1300 tokens. Note that the second component of the average shortest path length and vocabulary size (F ( l ) (2) and F ( M ) (2) ) are relevant as they appear at the top of the tree. Table 4.…”
Section: Stylistic Variation Among Booksmentioning
confidence: 99%
See 1 more Smart Citation
“…Among the reasons behind the popularity of DFA was its ability of detecting fractal character of signals, which was subsequently extended to the multifractal case (the MFDFA method [17]), which also proved very useful if applied to empirical data [18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36], especially owing to its superior reliability if compared to other methods [37]. DCCA was also generalized in order to be applicable to signals with multifractal cross-correlations and the resulting MFDCCA/MFDXA algorithm [38] also attracted some attention [39][40][41][42].…”
Section: Introductionmentioning
confidence: 99%
“…We should really distinguish two important movements. First, the 'Econophysics' movement which applies formalisms from statistical mechanics to the social sciences, and championed by Eugene Stanley and others (for instance [1][2][3][4][5][6]). Second, the movement which applies the mathematical apparatus from quantum information to the cognitive and social sciences, and championed by Andrei khrennikov and others (see [7][8][9][10][11][12]).…”
Section: Introductionmentioning
confidence: 99%