Shannon entropy in time-varying semantic networks of titles of scientific paper

Marcelo Do Vale Cunha,Marcelo Albano Moret,Hernane Borges De Barros Pereira,Carlos Cesar Ribeiro Santos

doi:10.1007/s41109-020-00292-0

Abstract

Recent work has employed information theory in social and complex networks. Studies often discuss entropy in the degree distributions of a network. However, no specific work on entropy exists in clique networks. This work is an extension of a previous study that discussed this topic. We propose a method for calculating the entropy of a clique network and its minimum and maximum values in temporal semantic networks based on titles of scientific papers. In addition, the critical network of moments was extracted. We use the titles of scientific papers published in Nature and Science over ten-year period. The results show the diversity of vocabulary over time, based on the entropy values of vertices and edges. In each critical network, we discover the paths that connect important words and an interesting modular structure.

Highlights

Information theory has evolved in recent decades and has been applied in different fields, such as biology, economics and quantum confined systems (Mousavian et al 2016; Mishra and Ayyub 2019; Nascimento and Prudente 2018; Brillouin 2013)
According to the definition provided in Grilo et al (2017) and the premise of (Caldeira et al 2006), we consider a semantic network of cliques as a system of knowledge representation established by a specific context and imbued with functionality intention, where the vertices are words, concepts or entities with semantic meaning and the smallest unit of meaning is the sentence and the edges consist of connections between two words that appear in the sentence
Building a time-varying semantic network of titles (TVSNT) The Semantic network of titles (SNT) is modeled for a time-varying graph (TVG), where V is the set of different words and E is the set of pairs of words in the same title; is the collected period, which is given in weeks, since a week is the minimum period of publication of the journals

Summary

Introduction

Information theory has evolved in recent decades and has been applied in different fields, such as biology, economics and quantum confined systems (Mousavian et al 2016; Mishra and Ayyub 2019; Nascimento and Prudente 2018; Brillouin 2013). According to the definition provided in Grilo et al (2017) and the premise of (Caldeira et al 2006), we consider a semantic network of cliques as a system of knowledge representation established by a specific context and imbued with functionality intention, where the vertices are words, concepts or entities with semantic meaning and the smallest unit of meaning is the sentence (e.g., a phrase of a text or discourse, title of a scientific paper, and keywords of a paper) and the edges consist of connections between two words that appear in the sentence. The network displays the most information with the least residue (Teixeira et al 2010); Nascimento et al (2016) analyzed a semantic network formed by the keywords of a (2020) 5:53

Methods

Results

Conclusion