Language Time Series Analysis

Details Language Time Series Analysis Language Time Series Analysis

2006-07-11

arxiv.org/abs/physics/0607095v1

Physics

Physics and Society

21 pages, 5 figures, accepted in Physica A

Scientific paper

10.1016/j.physa.2006.02.042

We use the Detrended Fluctuation Analysis (DFA) and the Grassberger-Proccacia analysis (GP) methods in order to study language characteristics. Despite that we construct our signals using only word lengths or word frequencies, excluding in this way huge amount of information from language, the application of Grassberger- Proccacia (GP) analysis indicates that linguistic signals may be considered as the manifestation of a complex system of high dimensionality, different from random signals or systems of low dimensionality such as the earth climate. The DFA method is additionally able to distinguish a natural language signal from a computer code signal. This last result may be useful in the field of cryptography.

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