This volume explores the universal mathematical properties underlying
big language data and possible reasons why such properties exist,
revealing how we may be unconsciously mathematical in our language use.
These properties are statistical and thus different from linguistic
universals that contribute to describing the variation of human
languages, and they can only be identified over a large accumulation of
usages. The book provides an overview of state-of-the art findings on
these statistical universals and reconsiders the nature of language
accordingly, with Zipf's law as a well-known example.
The main focus of the book further lies in explaining the property of
long memory, which was discovered and studied more recently by borrowing
concepts from complex systems theory. The statistical universals not
only possibly lie as the precursor of language system formation, but
they also highlight the qualities of language that remain weak points in
today's machine learning.
In summary, this book provides an overview of language's global
properties. It will be of interest to anyone engaged in fields related
to language and computing or statistical analysis methods, with an
emphasis on researchers and students in computational linguistics and
natural language processing. While the book does apply mathematical
concepts, all possible effort has been made to speak to a
non-mathematical audience as well by communicating mathematical content
intuitively, with concise examples taken from real texts.
