Rank-frequency relation for Chinese characters
This work provides insights into linguistic patterns for researchers in computational linguistics and text analysis, though it is incremental as it extends known laws to a new domain.
The study demonstrates that Zipf's law holds for Chinese characters in short texts, similar to English words, and reveals a two-layer structure in long texts with a power-law regime for frequent characters and an exponential-like regime for less frequent ones, including hapax legomena.
We show that the Zipf's law for Chinese characters perfectly holds for sufficiently short texts (few thousand different characters). The scenario of its validity is similar to the Zipf's law for words in short English texts. For long Chinese texts (or for mixtures of short Chinese texts), rank-frequency relations for Chinese characters display a two-layer, hierarchic structure that combines a Zipfian power-law regime for frequent characters (first layer) with an exponential-like regime for less frequent characters (second layer). For these two layers we provide different (though related) theoretical descriptions that include the range of low-frequency characters (hapax legomena). The comparative analysis of rank-frequency relations for Chinese characters versus English words illustrates the extent to which the characters play for Chinese writers the same role as the words for those writing within alphabetical systems.