Synopsis

The Value of Circular Definitions

Physics 5, s148
Methods from statistical physics and graph theory help uncover the structure of human language.
D. Levary et al., Phys. Rev. X (2012)

More than one reader has looked up a word in a dictionary, turned to a word used in the definition, only to be eventually pointed back to the original word in a loop of circular definitions. As annoying as this might sometimes be, such loops offer insights into the structure of a language and the expansion of its lexicon. David Levary, of Harvard University, and colleagues report in Physical Review X their use of methods from graph theory and statistical physics to study networks of words in dictionaries and show that creation of these loops is a fundamental mechanism in the growth of a language.

The authors looked at the words in a database called WordNet, treating them as nodes in a graph structure connected by directional links (that is, the link points to words used in the definition). Levary et al. show both theoretically and from watching how nodes are incorporated into the graph that new concepts can only be introduced by adding a loop to the network. They also discovered that words in a given loop often were introduced into the language at about the same time. When the dates of origin of words in a loop differ greatly, it typically indicates a fundamental change in a word’s meaning after its earlier introduction.

Levary et al. further found that new words preferentially attach to existing words with a large number of links pointing to them, a kind of linguistic “rich get richer” behavior. This matches our intuition that new words are defined in terms of well-used common words for better understandability. Taken together, the results suggest that such techniques from physics and graph theory could be a valuable forensic tool for uncovering the deeper workings of human communication and the evolution of language. – David Voss


Subject Areas

Interdisciplinary PhysicsStatistical Physics

Related Articles

Network Science Applied to Urban Transportation
Computational Physics

Network Science Applied to Urban Transportation

A simple model based on network theory can reproduce the complex structures seen in urban transportation networks. Read More »

Strange Kinetics Shape Network Growth
Statistical Physics

Strange Kinetics Shape Network Growth

A connection between time-varying networks and transport theory opens prospects for developing predictive equations of motion for networks. Read More »

Improving Assessments of Climate Tipping Points
Complex Systems

Improving Assessments of Climate Tipping Points

Statistical properties of fluctuations of certain parameters describing a complex system can reveal when that system is approaching a tipping point. Read More »

More Articles