arXiv · 1105.1306
Excess entropy in natural language: present state and perspectives
Abstract
We review recent progress in understanding the meaning of mutual information in natural language. Let us define words in a text as strings that occur sufficiently often. In a few previous papers, we have shown that a power-law distribution for so defined words (a.k.a. Herdan's law) is obeyed if there is a similar power-law growth of (algorithmic) mutual information between adjacent portions of texts of increasing length. Moreover, the power-law growth of information holds if texts describe a complicated infinite (algorithmically) random object in a highly repetitive way, according to an analogous power-law distribution. The described object may be immutable (like a mathematical or physical constant) or may evolve slowly in time (like cultural heritage). Here we reflect on the respective mathematical results in a less technical way. We also discuss feasibility of deciding to what extent these results apply to the actual human communication.
Explore related subjects
Keep this discovery
Łukasz Dębowski. 2011-05-06. Excess entropy in natural language: present state and perspectives. https://doi.org/10.1063/1.3630929
Cite the original work for its findings. Save a collection to share your selection of sources.