Exploring the law of text geographic information

TL;DR

This paper investigates the distribution patterns of textual geographic information, hypothesizing and confirming its conformity to the Gamma distribution across diverse datasets, and explores implications for human utilization and extraction methods.

Contribution

It introduces the hypothesis that geographic information follows the Gamma distribution and provides empirical evidence across multiple datasets, challenging traditional distribution assumptions.

Findings

Geographic information conforms to the Gamma distribution.

Traditional laws like Gaussian and Zipf's law are refuted in this context.

Estimated upper bounds of human utilization of geographic information.

Abstract

Textual geographic information is indispensable and heavily relied upon in practical applications. The absence of clear distribution poses challenges in effectively harnessing geographic information, thereby driving our quest for exploration. We contend that geographic information is influenced by human behavior, cognition, expression, and thought processes, and given our intuitive understanding of natural systems, we hypothesize its conformity to the Gamma distribution. Through rigorous experiments on a diverse range of 24 datasets encompassing different languages and types, we have substantiated this hypothesis, unearthing the underlying regularities governing the dimensions of quantity, length, and distance in geographic information. Furthermore, theoretical analyses and comparisons with Gaussian distributions and Zipf's law have refuted the contingency of these laws. Significantly, we have estimated the upper bounds of human utilization of geographic information, pointing towards the existence of uncharted territories. Also, we provide guidance in geographic information extraction. Hope we peer its true countenance uncovering the veil of geographic information.