The network of concepts in written texts

Abstract

Complex network theory is used to investigate the structure of meaningful concepts in written texts of individual authors. Networks have been constructed after a two phase filtering, where words with less meaning contents are eliminated, and all remaining words are set to their canonical form, without any number, gender or time flexion. Each sentence in the text is added to the network as a clique. A large number of written texts have been scrutinized, and its found that texts have small-world as well as scale-free structures. The growth process of these networks has also been investigated, and a universal evolution of network quantifiers have been found among the set of texts written by distinct authors. Further analyzes, based on shufling procedures taken either on the texts or on the constructed networks, provide hints on the role played by the word frequency and sentence length distributions to the network structure. Since the meaningful words are related to concepts in the author's mind, results for text networks may uncover patterns in communication and language processes that occur in the mind.

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Cited by in corpus (11)

• Analyzing and Modeling Real-World Phenomena with Complex Networks: A Survey of Applications
• Evolving small-world scale-free networks consist of cliques
• Complex network analysis of literary and scientific texts
• Characteristics of Real Futures Trading Networks
• Network analysis of a corpus of undeciphered Indus civilization inscriptions indicates syntactic organization
• Modeling Discrete Combinatorial Systems as Alphabetic Bipartite Networks: Theory and Applications
• Estimating Subgraph Frequencies with or without Attributes from Egocentrically Sampled Data
• Inflection system of a language as a complex network
• Dependencies: Formalising Semantic Catenae for Information Retrieval
• Compactified Horizontal Visibility Graph for the Language Network
• A model of language inflection graphs