Journal of Quantitative Linguistics

Aims & Scope

Journal of Quantitative Linguistics is an international forum for the publication and discussion of research on the quantitative characteristics of language and text in an exact mathematical form.

This approach, which is of growing interest, opens up important and exciting theoretical perspectives, as well as solutions for a wide range of practical problems such as machine learning or statistical parsing, by introducing into linguistics the methods and models of advanced scientific disciplines such as the natural sciences, economics, and psychology.

Specifically, JQL publishes on: Observations and descriptions of all aspects of language and text phenomena including the areas of psycholinguistics, sociolinguistics, dialectology, pragmatics, etc. as far as they use quantitative mathematical methods (probability theory, stochastic processes, differential and difference equations, fuzzy logics and set theory, function theory etc.), on all levels of linguistic analysis.

Applications of methods, models, or findings from quantitative linguistics to problems of natural language processing, machine translation, language teaching, documentation and information retrieval.

Methodological problems of linguistic measurement, model construction, sampling and test theory.

Epistemological issues such as explanation of language and text phenomena, contributions to theory construction, systems theory, philosophy of science.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	1.7

SJR (SCImago Journal Rank)

Year	Value
2024	0.596

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	33

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Social Sciences, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Cutting the Gordian Knot: The Moving-Average Type–Token Ratio (MATTR)

  Citation: 281

  Authors: Michael A., Joe D.

• Binomial Confidence Intervals and Contingency Tests: Mathematical Fundamentals and the Evaluation of Alternative Methods

  Citation: 247

  Authors: Sean

• Good‐turing frequency estimation without tears*

  Citation: 167

  Authors: William A., Geoffrey

• Two Regimes in the Frequency of Words and the Origins of Complex Lexicons: Zipf’s Law Revisited^∗

  Citation: 146

  Authors: Ramon, Ricard V.

• On Round Numbers: Pragmatic Aspects of Numerical Expressions

  Citation: 82

  Authors: C.J.M., M.M.W.

• Dynamics of Text Generation with Realistic Zipf's Distribution

  Citation: 78

  Authors: Damián, Marcelo

• New Machine Learning Methods Demonstrate the Existence of a Human Stylome

  Citation: 67

  Authors: Hans, Harald, Fiona, Marco, Anneke

• Can Type-Token Ratio be Used to Show Morphological Complexity of Languages?

  Citation: 66

  Authors: Kimmo

• Towards a theory of word length distribution*

  Citation: 60

  Authors: Gejza, Reinhard, Rüdiger, Gabriel

• Measuring linguistic complexity: The morphological tier

  Citation: 59

  Authors: Patrick

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