  Zipf's law has been found in many human-related fields, including language,
where the frequency of a word is persistently found as a power law function of
its frequency rank, known as Zipf's law. However, there is much dispute whether
it is a universal law or a statistical artifact, and little is known about what
mechanisms may have shaped it. To answer these questions, this study conducted
a large scale cross language investigation into Zipf's law. The statistical
results show that Zipf's laws in 50 languages all share a 3-segment structural
pattern, with each segment demonstrating distinctive linguistic properties and
the lower segment invariably bending downwards to deviate from theoretical
expectation. This finding indicates that this deviation is a fundamental and
universal feature of word frequency distributions in natural languages, not the
statistical error of low frequency words. A computer simulation based on the
dual-process theory yields Zipf's law with the same structural pattern,
suggesting that Zipf's law of natural languages are motivated by common
cognitive mechanisms. These results show that Zipf's law in languages is
motivated by cognitive mechanisms like dual-processing that govern human verbal
behaviors.
