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Words are fundamental linguistic units that connect thoughts and things through meaning. However, words do not appear independently in a text sequence. The existence of syntactic rules induces correlations among neighboring words. Using an ordinal pattern approach, we present an analysis of lexical statistical connections for 11 major languages. We find that the diverse manners that languages utilize to express word relations give rise to unique pattern structural distributions. Furthermore, fluctuations of these pattern distributions for a given language can allow us to determine both the historical period when the text was written and its author. Taken together, our results emphasize the relevance of ordinal time series analysis in linguistic typology, historical linguistics, and stylometry.
FOS: Computer and information sciences, Physics - Physics and Society, Computer Science - Computation and Language, Statistical Mechanics (cond-mat.stat-mech), ORDINAL PATTERNS, Physics, LANGUAGE, FOS: Physical sciences, Physics and Society (physics.soc-ph), Physics and Society, SYNTACTIC RULES, Statistical Mechanics, https://purl.org/becyt/ford/1.3, Computer Science, Computation and Language, https://purl.org/becyt/ford/1, Computation and Language (cs.CL), Condensed Matter - Statistical Mechanics, LEXICAL PATTERNS
FOS: Computer and information sciences, Physics - Physics and Society, Computer Science - Computation and Language, Statistical Mechanics (cond-mat.stat-mech), ORDINAL PATTERNS, Physics, LANGUAGE, FOS: Physical sciences, Physics and Society (physics.soc-ph), Physics and Society, SYNTACTIC RULES, Statistical Mechanics, https://purl.org/becyt/ford/1.3, Computer Science, Computation and Language, https://purl.org/becyt/ford/1, Computation and Language (cs.CL), Condensed Matter - Statistical Mechanics, LEXICAL PATTERNS
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