---
title: "Multifractal analysis of sentence lengths in English literary texts"
description: "The paper asks whether the rhythm of sentence lengths in English fiction has fractal or multifractal structure, meaning… 28 references."
authors: ["Iwona Grabska-Gradzinska", "Andrzej Kulig", "Jaros\\law Kwapien", "Pawe\\l Oswi\\kecimka", "Stanis\\law Drozdz"]
year: 2012
venue: "arXiv:1212.3171 · AWERProcedia Information Technology & Computer Science 03, 1700, 2013"
source: "https://arxiv.org/abs/1212.3171"
doi: "10.48550/arxiv.1212.3171"
arxiv: "1212.3171"
licence: "arXiv — non-exclusive license to distribute"
licence_url: "http://arxiv.org/licenses/nonexclusive-distrib/1.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/grabska-gradzinska-2012-multifractal-analysis-sentence-lengths-english/"
---
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# Multifractal analysis of sentence lengths in English literary texts

**Authors:** Iwona Grabska-Gradzinska, Andrzej Kulig, Jaros\\law Kwapien, Pawe\\l Oswi\\kecimka and Stanis\\law Drozdz · **Year:** 2012 · **Venue:** arXiv:1212.3171 · AWERProcedia Information Technology & Computer Science 03, 1700, 2013 · **Licence:** [arXiv — non-exclusive license to distribute](http://arxiv.org/licenses/nonexclusive-distrib/1.0/)

**Links:** [Publisher's page](https://arxiv.org/abs/1212.3171) · [PDF](https://arxiv.org/pdf/1212.3171) · [DOI 10.48550/arxiv.1212.3171](https://doi.org/10.48550/arxiv.1212.3171) · [arXiv 1212.3171](https://arxiv.org/abs/1212.3171) · [OpenAlex](https://openalex.org/W2157650680)

**Citations:** 7 citations (OpenAlex, 2026-10-14)

## Summary
The paper asks whether the rhythm of sentence lengths in English fiction has fractal or multifractal structure, meaning nonlinear long-range dependence rather than only linear correlation. The authors took 30 literary books from Project Gutenberg. They converted each book into a sequence of sentence lengths counted in words, preserving the original order. Sentence boundaries were full stops, colons, semicolons, question marks and exclamation marks; commas were ignored. The main tool was MFDFA, and WTMM served as a cross-check. Shuffled versions of each series acted as surrogates to separate genuine multifractality from artifacts caused by heavy tails or nonstationarity.

Each text was placed in one of four groups: no fractal scaling, monofractal, spurious multifractal-like behaviour at small scales, or genuinely multifractal. Most books were not multifractal, and some showed no scaling at all. Only a handful qualified as true multifractals. This tempers the broader claims about the fractal nature of language and shows how carefully such signals must be read.

## Key points
- The corpus has 30 English books, which the paper attributes to 17 authors. They include 5 by Dickens, 4 by Austen, and 3 each by Joyce, Conan Doyle and Twain. Single works come from Wilde, Christie, Melville, Carroll, Darwin, Shelley, Stoker and others.
- The shortest signal is *Alice in Wonderland*. The longest are *Ulysses* and *Bleak House*.
- Sentence-length distributions can be leptokurtic, so the Rényi parameter q was limited to −3…3.
- A text counted as multifractal if its singularity spectrum f(α) was clearly wider than about 0.1. The authors say this threshold comes from their own experience.
- Results from MFDFA and WTMM agreed more closely as the evidence for multifractality grew stronger.
- Only the genuinely multifractal example showed a power-law stretch in its autocorrelation function.
- Twain's and Conan Doyle's books had fairly stable fractal properties from one book to another, whereas Austen's books differed among themselves.

## Interesting ideas
- Every text is compared against a shuffled copy of itself, and multifractality counts only if it clearly exceeds what the shuffled copy shows. This kind of null baseline exposes effects that come merely from the value distribution.
- A primary method is paired with a weaker independent one, and confidence rises when the two agree. The weaker method alone is avoided because it is unreliable on short inputs.
- Results are sorted into four outcome classes rather than a yes/no verdict, one of which is an explicit "looks positive but is spurious" class. This keeps borderline artifacts from being counted as successes.
- Sentence units are cut at colons and semicolons as well as terminal punctuation, on the view that each unit carries a distinct piece of information, while commas are deliberately excluded.
- The range of moments is restricted when the data are heavy-tailed, since extreme values would otherwise dominate the statistics.

## For Mova

How these ideas could serve Mova, our small open language model — its files, stages and tests:

- **I1** (learn): Evaluations could be rerun on inputs with shuffled sentences or clauses, so that any gain that survives the shuffle is flagged as not depending on discourse order.
- **I2** (learn): Silver labels from witness parsers could be weighted by cross-method agreement, and a witness known to be weak on short sentences could be given less trust there.
- **I3** (learn): Self-induced repair rules could be judged with a similar graded outcome set, which would separate rules that truly help from ones that only appear helpful on easy cases.
- **I4** (tokens): The sentence splitter could expose a configurable segmentation level, with clause-like chunks at ";" and ":", for downstream steps that want smaller information units.
- **I5** (learn): When computing aggregate metrics over corpora with very long sentences, robust or clipped statistics could stop a few outliers from distorting parser comparisons.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

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## Cite

Cite as: Iwona Grabska-Gradzinska, Andrzej Kulig, Jaros\\law Kwapien, Pawe\\l Oswi\\kecimka and Stanis\\law Drozdz. 2012. Multifractal analysis of sentence lengths in English literary texts. arXiv:1212.3171 · AWERProcedia Information Technology & Computer Science 03, 1700, 2013.

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@misc{grabskagradzinska2012multifractal,
  title = {{Multifractal analysis of sentence lengths in English literary texts}},
  author = {Iwona Grabska-Gradzinska, Andrzej Kulig, Jaroslaw Kwapien, Pawel Oswikecimka and Stanislaw Drozdz},
  year = {2012},
  doi = {10.48550/arxiv.1212.3171},
  eprint = {1212.3171},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.48550/arxiv.1212.3171}
}
```

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## References

28 references, 0 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. M.H. Christiansen, N. Chater, Language as shaped by the brain, Behav. Brain Sci. vol. 31, pp. 489-509 (2008) [find](https://scholar.google.com/scholar?q=M%2EH%2E+Christiansen%2C+N%2E+Chater%2C+Language+as+shaped+by+the+brain%2C+Behav%2E+Brain+Sci%2E+vol%2E+31%2C+pp%2E+489%2D509+%282008%29)
2. J. Kwapień, S. Drożdż, Physical approach to complex systems, Phys. Rep. vol. 515, pp. 115-226 (2012) [find](https://scholar.google.com/scholar?q=J%2E+Kwapie%C5%84%2C+S%2E+Dro%C5%BCd%C5%BC%2C+Physical+approach+to+complex+systems%2C+Phys%2E+Rep%2E+vol%2E+515%2C+pp%2E+115%2D226+%282012%29)
3. R. Ferrer-i-Cancho, R.V. Solé, Two regimes in the frequency of words and the origins of complex lexicons: Zipf’s law revisited, J. Quant. Ling. vol. 8, pp. 165-173 (2001) [find](https://scholar.google.com/scholar?q=R%2E+Ferrer%2Di%2DCancho%2C+R%2EV%2E+Sol%C3%A9%2C+Two+regimes+in+the+frequency+of+words+and+the+origins+of+complex+lexicons%3A+Zipf%E2%80%99s+law+revisited%2C+J%2E+Quant%2E+Ling%2E+vol%2E+8%2C+pp%2E+165%2D173+%282001%29)
4. L. Lü, Z.-K. Zhang, T. Zhou, Scaling laws in human language, preprint arXiv:1202.2903 (2012) [↗](https://arxiv.org/abs/1202.2903)
5. B. Corominas-Murtra, J. Fortuny, R.V. Solé, Emergence of Zipfs law in the evolution of communication, Phys. Rev. E vol. 83, no. 036115 (2011) [find](https://scholar.google.com/scholar?q=B%2E+Corominas%2DMurtra%2C+J%2E+Fortuny%2C+R%2EV%2E+Sol%C3%A9%2C+Emergence+of+Zipfs+law+in+the+evolution+of+communication%2C+Phys%2E+Rev%2E+E+vol%2E+83%2C+no%2E+036115+%282011%29)
6. M.E.J. Newman, Power laws, Pareto distributions and Zipf’s law, Cont. Phys. vol. 45, pp. 323-351 (2005) [find](https://scholar.google.com/scholar?q=M%2EE%2EJ%2E+Newman%2C+Power+laws%2C+Pareto+distributions+and+Zipf%E2%80%99s+law%2C+Cont%2E+Phys%2E+vol%2E+45%2C+pp%2E+323%2D351+%282005%29)
7. S.K. Baek, S. Bernhardsson, P. Minnhagen, Zipf’s law unzipped, New J. Phys. vol. 4, no. 043004 (2011) [find](https://scholar.google.com/scholar?q=S%2EK%2E+Baek%2C+S%2E+Bernhardsson%2C+P%2E+Minnhagen%2C+Zipf%E2%80%99s+law+unzipped%2C+New+J%2E+Phys%2E+vol%2E+4%2C+no%2E+043004+%282011%29)
8. I. Grabska-Gradzińska, A. Kulig, J. Kwapień, S. Drożdż, Complex network analysis of literary and scientific texts, Int. J. Mod. Phys. Vol. 23, no. 7 (2012) [find](https://scholar.google.com/scholar?q=I%2E+Grabska%2DGradzi%C5%84ska%2C+A%2E+Kulig%2C+J%2E+Kwapie%C5%84%2C+S%2E+Dro%C5%BCd%C5%BC%2C+Complex+network+analysis+of+literary+and+scientific+texts%2C+Int%2E+J%2E+Mod%2E+Phys%2E+Vol%2E+23%2C+no%2E+7+%282012%29)
9. C.G. Nevill-Manning, I.H. Witten, Identifying hierarchical structure in sequences: a linear-time algorithm, J. Artif. Intell. Res. vol. 7, pp. 67-82 (1997) [find](https://scholar.google.com/scholar?q=C%2EG%2E+Nevill%2DManning%2C+I%2EH%2E+Witten%2C+Identifying+hierarchical+structure+in+sequences%3A+a+linear%2Dtime+algorithm%2C+J%2E+Artif%2E+Intell%2E+Res%2E+vol%2E+7%2C+pp%2E+67%2D82+%281997%29)
10. W. Ebeling, T. Pöschel, Entropy and long range correlations in literary English, Europhys. Lett. vol.26, pp.241-246 (1994) [find](https://scholar.google.com/scholar?q=W%2E+Ebeling%2C+T%2E+P%C3%B6schel%2C+Entropy+and+long+range+correlations+in+literary+English%2C+Europhys%2E+Lett%2E+vol%2E26%2C+pp%2E241%2D246+%281994%29)
11. J.M. Hausdorff, P.L. Purdon, C.-K. Peng, Z. Ladin, J.Y. Wei, A.L. Goldberger, Fractal dynamics of human gait: stability of long-range correlations in stride interval fluctuations, J. Appl. Physiol. vol. 80, pp. 1448-1457 (1996) [find](https://scholar.google.com/scholar?q=J%2EM%2E+Hausdorff%2C+P%2EL%2E+Purdon%2C+C%2E%2DK%2E+Peng%2C+Z%2E+Ladin%2C+J%2EY%2E+Wei%2C+A%2EL%2E+Goldberger%2C+Fractal+dynamics+of+human+gait%3A+stability+of+long%2Drange+correlations+in+stride+interval+fluctuations%2C+J%2E+Appl%2E+Physiol%2E+vo)
12. M.P. Paulus, M.A. Geyer, D.L. Braff, Long-range correlations in choice sequences of schizophrenic patients, Schi. Res. vol. 35, pp. 69-75 (1999) [find](https://scholar.google.com/scholar?q=M%2EP%2E+Paulus%2C+M%2EA%2E+Geyer%2C+D%2EL%2E+Braff%2C+Long%2Drange+correlations+in+choice+sequences+of+schizophrenic+patients%2C+Schi%2E+Res%2E+vol%2E+35%2C+pp%2E+69%2D75+%281999%29)
13. K. Linkenkaer-Hansen, V.V. Nikouline, J.M. Palva, R.J. Ilmoniemi, Long-range temporal correlations and scaling behavior in human brain oscillations, J. Neurosci. vol. 21, pp. 1370-1377 (2001) [find](https://scholar.google.com/scholar?q=K%2E+Linkenkaer%2DHansen%2C+V%2EV%2E+Nikouline%2C+J%2EM%2E+Palva%2C+R%2EJ%2E+Ilmoniemi%2C+Long%2Drange+temporal+correlations+and+scaling+behavior+in+human+brain+oscillations%2C+J%2E+Neurosci%2E+vol%2E+21%2C+pp%2E+1370%2D1377+%282001%29)
14. K. Torre, R. Balasubramaniam, N. Rheaume, L. Lemoine, H.N. Zelaznik, Long-range correlation properties in motor timing are individual and task specific, Psychon. Bull. Rev. vol. 18, pp. 339-346 (2011) [find](https://scholar.google.com/scholar?q=K%2E+Torre%2C+R%2E+Balasubramaniam%2C+N%2E+Rheaume%2C+L%2E+Lemoine%2C+H%2EN%2E+Zelaznik%2C+Long%2Drange+correlation+properties+in+motor+timing+are+individual+and+task+specific%2C+Psychon%2E+Bull%2E+Rev%2E+vol%2E+18%2C+pp%2E+339%2D346+%282011%29)
15. J. Gillet, M. Ausloos, A comparison of natural (English) and artificial (esperanto) languages. A multifractal method based analysis, preprint arXiv:0801.2510 (2008) [↗](https://arxiv.org/abs/0801.2510)
16. W. Ebeling, A. Neiman, Long-range correlations between letters and sentences in texts, Physica A vol. 215, pp. 233-241 (1995) [find](https://scholar.google.com/scholar?q=W%2E+Ebeling%2C+A%2E+Neiman%2C+Long%2Drange+correlations+between+letters+and+sentences+in+texts%2C+Physica+A+vol%2E+215%2C+pp%2E+233%2D241+%281995%29)
17. L. Hřebiček, Persistence and other aspects of sentence-length series, J. Quant. Ling. vol. 4, pp. 105-109 (1997) [find](https://scholar.google.com/scholar?q=L%2E+H%C5%99ebi%C4%8Dek%2C+Persistence+and+other+aspects+of+sentence%2Dlength+series%2C+J%2E+Quant%2E+Ling%2E+vol%2E+4%2C+pp%2E+105%2D109+%281997%29)
18. M.A. Montemurro, P.A. Pury, Long-range correlations in literary corpora, Fractals vol. 10, pp. 451-461 (2002) [find](https://scholar.google.com/scholar?q=M%2EA%2E+Montemurro%2C+P%2EA%2E+Pury%2C+Long%2Drange+correlations+in+literary+corpora%2C+Fractals+vol%2E+10%2C+pp%2E+451%2D461+%282002%29)
19. S.S. Melnyk, O.V. Usatenko, V.A. Yampol’skii, Competition between two kinds of correlations in literary texts, Phys. Rev. E vol. 72, no. 026140 (2005) [find](https://scholar.google.com/scholar?q=S%2ES%2E+Melnyk%2C+O%2EV%2E+Usatenko%2C+V%2EA%2E+Yampol%E2%80%99skii%2C+Competition+between+two+kinds+of+correlations+in+literary+texts%2C+Phys%2E+Rev%2E+E+vol%2E+72%2C+no%2E+026140+%282005%29)
20. G. Sahin, M. Erentürk, A. Hacinliyan, Detrended fluctuation analysis in natural languages using non-corpus parametrization, Chaos Solit. Fract. vol. 41, pp. 198-205 (2009) [find](https://scholar.google.com/scholar?q=G%2E+Sahin%2C+M%2E+Erent%C3%BCrk%2C+A%2E+Hacinliyan%2C+Detrended+fluctuation+analysis+in+natural+languages+using+non%2Dcorpus+parametrization%2C+Chaos+Solit%2E+Fract%2E+vol%2E+41%2C+pp%2E+198%2D205+%282009%29)
21. J. Bhan, S. Kim, J. Kim, Y. Kwon, S. Yang, K. Lee, "Long-range correlations in Korean literary corpora, Chaos Solit. Fract. vol. 29, pp. 69-81 (2006) [find](https://scholar.google.com/scholar?q=J%2E+Bhan%2C+S%2E+Kim%2C+J%2E+Kim%2C+Y%2E+Kwon%2C+S%2E+Yang%2C+K%2E+Lee%2C+%22Long%2Drange+correlations+in+Korean+literary+corpora%2C+Chaos+Solit%2E+Fract%2E+vol%2E+29%2C+pp%2E+69%2D81+%282006%29)
22. C.-K. Peng, S.V. Buldyrev, S. Havlin, M. Simons, H.E. Stanley, A.L. Goldberger, Mosaic organization of DNA nucleotides, Phys. Rev. E vol. 49, pp. 1685-1689 (1994) [find](https://scholar.google.com/scholar?q=C%2E%2DK%2E+Peng%2C+S%2EV%2E+Buldyrev%2C+S%2E+Havlin%2C+M%2E+Simons%2C+H%2EE%2E+Stanley%2C+A%2EL%2E+Goldberger%2C+Mosaic+organization+of+DNA+nucleotides%2C+Phys%2E+Rev%2E+E+vol%2E+49%2C+pp%2E+1685%2D1689+%281994%29)
23. A.N. Pavlov, W. Ebeling, L. Molgedey, A.R. Ziganshin, V.S. Anishchenko, Scaling features of texts, images and time series, Physica A vol. 300, pp. 310-324 (2001) [find](https://scholar.google.com/scholar?q=A%2EN%2E+Pavlov%2C+W%2E+Ebeling%2C+L%2E+Molgedey%2C+A%2ER%2E+Ziganshin%2C+V%2ES%2E+Anishchenko%2C+Scaling+features+of+texts%2C+images+and+time+series%2C+Physica+A+vol%2E+300%2C+pp%2E+310%2D324+%282001%29)
24. J.W. Kantelhardt, S.A. Zschiegner, E. Koscielny-Bunde, S. Havlin, A. Bunde, H.E. Stanley, Multifractal detrended fluctuation analysis of nonstationary time series, Physica A vol. 316, pp. 87-114 (2002) [find](https://scholar.google.com/scholar?q=J%2EW%2E+Kantelhardt%2C+S%2EA%2E+Zschiegner%2C+E%2E+Koscielny%2DBunde%2C+S%2E+Havlin%2C+A%2E+Bunde%2C+H%2EE%2E+Stanley%2C+Multifractal+detrended+fluctuation+analysis+of+nonstationary+time+series%2C+Physica+A+vol%2E+316%2C+pp%2E+87%2D114+%282002)
25. A. Arneodo, E. Bacry, J.F. Muzy, The thermodynamics of fractals revisited with wavelets, Physica A vol. 213-275, pp. 232 (1995) [find](https://scholar.google.com/scholar?q=A%2E+Arneodo%2C+E%2E+Bacry%2C+J%2EF%2E+Muzy%2C+The+thermodynamics+of+fractals+revisited+with+wavelets%2C+Physica+A+vol%2E+213%2D275%2C+pp%2E+232+%281995%29)
26. P. Oświęcimka, J. Kwapień, S. Drożdż, Wavelet versus detrended fluctuation analysis of multifractal structures, Phys. Rev. E vol. 74, no. 016103 (2006) [find](https://scholar.google.com/scholar?q=P%2E+O%C5%9Bwi%C4%99cimka%2C+J%2E+Kwapie%C5%84%2C+S%2E+Dro%C5%BCd%C5%BC%2C+Wavelet+versus+detrended+fluctuation+analysis+of+multifractal+structures%2C+Phys%2E+Rev%2E+E+vol%2E+74%2C+no%2E+016103+%282006%29)
27. T.C. Halsey, M.H. Jensen, L.P. Kadanoff, I. Procaccia, B.I. Shraiman, Fractal measures and their singularities: the characterization of strange sets, Phys. Rev. A vol. 33, pp. 1141-1151 (1986) [find](https://scholar.google.com/scholar?q=T%2EC%2E+Halsey%2C+M%2EH%2E+Jensen%2C+L%2EP%2E+Kadanoff%2C+I%2E+Procaccia%2C+B%2EI%2E+Shraiman%2C+Fractal+measures+and+their+singularities%3A+the+characterization+of+strange+sets%2C+Phys%2E+Rev%2E+A+vol%2E+33%2C+pp%2E+1141%2D1151+%281986%29)
28. S. Drożdż, J. Kwapień, P. Oświęcimka, R. Rak, Quantitative features of multifractal subtleties in time series, EPL vol. 88, no. 60003 (2009) [find](https://scholar.google.com/scholar?q=S%2E+Dro%C5%BCd%C5%BC%2C+J%2E+Kwapie%C5%84%2C+P%2E+O%C5%9Bwi%C4%99cimka%2C+R%2E+Rak%2C+Quantitative+features+of+multifractal+subtleties+in+time+series%2C+EPL+vol%2E+88%2C+no%2E+60003+%282009%29)

*Updated 24 October 2026*
