Topology of the conceptual network of language.

By Adilson E. Motter, Alessandro P. S. de Moura, Ying-Cheng Lai, Partha Dasgupta. Physical review. E, Statistical, nonlinear, and soft matter physics, 2002

310 citations recorded by the source corpus.

We define two words in a language to be connected if they express similar concepts. The network of connections among the many thousands of words that make up a language is important not only for the study of the structure and evolution of languages, but also for cognitive science. We study this issue quantitatively, by mapping out the conceptual network of the English language, with the connections being defined by the entries in a Thesaurus dictionary. We find that this network presents a small-world structure, with an amazingly small average shortest path, and appears to exhibit an asymptotic scale-free feature with algebraic connectivity distribution.

Subfields: Molecular Biology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/74e19b583c41e9792784e87d716f6443db1c78ae

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

In Statistical and Nonlinear Physics

Citations in the corpus

Analysis of weighted networks. (2004, methodology): “Networks of the co-occurrence of words in bodies of text have been studied by a number of authors recently [31, 32, 33], and are a useful quantitative tool for analyzing the semantic content of documents.”
Local Modeling of Attributed Graphs: Algorithms and Applications (2016, methodology): “[99] use a thesaurus to construct a network of synonyms, which they find to find to exhibit small world structure.”
Graph-of-word and TW-IDF: new approach to ad hoc IR (2013, background): “Similarly, an edge represents a meaningful relation between two vertices, either linguistic (e.g. syntactic [8] or semantic [18]) or statistical (e.g. co-occurrence [7]) depending on the use case.”
Implementing the iHOP concept for navigation of biomedical literature (2005, background): “We expect the exploration of this emerging network to be intuitive, since it is known that human memory is associative and that information is retrieved by connecting similar concepts (Koch and Laurent, 1999; Motter et al., 2002).”
The Structure and Function of Complex Networks (2003, result): “The network of relations between word classes in a thesaurus has been studied by Knuth [244] and more recently by various other authors [234, 304, 384].”
The “New” Science of Networks (2004, background): “What does it mean, for example, that any two And how is this relationship different from the same two words being connected through a short chain of semantic relationships (Motter et al. 2002)?”
Intermittency and scale-free networks: a dynamical model for human language complexity (2003, background): “Working along the same lines, other authors [21] found a “small world” topology [22], by looking at the number of synonyms in an English thesaurus, for each English lemma.”
Analyzing and modeling real-world phenomena with complex networks: a survey of applications (2007, background): “It was even suggested that assoc iative memory is originated in a process of efficiency maximization in the retrieval of infor mation (also related to the fact that the neural network is a small-world network) [419].”