Benford's Law and First Letter of Word

Abstract

A universal First-Letter Law (FLL) is derived and described. It predicts the percentages of first letters for words in novels. The FLL is akin to Benford's law (BL) of first digits, which predicts the percentages of first digits in a data collection of numbers. Both are universal in the sense that FLL only depends on the numbers of letters in the alphabet, whereas BL only depends on the number of digits in the base of the number system. The existence of these types of universal laws appears counter-intuitive. Nonetheless both describe data very well. Relations to some earlier works are given. FLL predicts that an English author on the average starts about 16 out of 100 words with the English letter `t'. This is corroborated by data, yet an author can freely write anything. Fuller implications and the applicability of FLL remain for the future.

arXiv comment10 pages, 11 figures

References in corpus (6)

• Zipf's law unzipped
• Neutral theory of chemical reaction networks
• Maximum Entropy, Word-Frequency, Chinese Characters, and Multiple Meanings
• Randomness versus specifics for word-frequency distributions
• The Dependence of Frequency Distributions on Multiple Meanings of Words, Codes and Signs
• The likely determines the unlikely

Cited by in corpus (2)

• The Newcomb-Benford law: Scale invariance and a simple Markov process based on it
• On the validation of Newcomb-Benford law and Weibull distribution in neuromuscular transmission