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Fractals in Language

Utilizing Big Data and digital tools, we know that language is self-similar at every level and across all different levels of scale. This is patterned in the form of the nonlinear asymptotic hyperbolic curve, which has been shown to occur with both lexical and phonetic items in language with data from the Linguistic Atlas project (Kretzschmar 2009, 2015). These linguistic fractals (or A-curves) match the way people use language in any given context and can be used to predict different outcomes for language use and variation.

Fractals and Complexity

Fractals are a major part of the underlying nature of complexity science. They occur because of the interaction emerging in any given complex system. Fractals are self-similar at every level; some examples are tree branches, leaf structures, the retina, and coastlines. Fractals are also part of the complex system of language, in every aspect of language in the form of nonlinear asymptotic hyperbolic curves.

Wolfram's Four Classes of One-Dimensional Cellular Automata

Wolfram: Four Classes of One-Dimensional Cellular Automata Stephen Wolfram studied the behavior of cellular automata in the simplest form possible, looking at one-dimensional, two-state cellular automata, either on or off, 1 or 0. This means that each cell is connected only to its two nearest neighbors. From this, he studied all the possible combinations of states, listed in binary. One example of this is the string 01101110, which is equal to the number 110 in decimal. He called this behavior Rule 110. Rule 30 is another example, from the string 00011110.

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