Network Analysis of Publications on Topological Indices from the Web of Science

Abstract

In this paper we analyze a collection of bibliographic networks, constructed from the data from the Web of Science on works (papers, books, etc.) on the topic of topological indices and on relating scientific fields. We present the general outlook and more specific findings about authors, works and journals, subtopics and keywords and also important relations between them based on scientometric approaches like the strongest and main citation paths, the main themes on citation path based on keywords, results of co-authorship analysis in form of the most prominent islands of citing authors, groups of collaborating authors, two-mode cores of authors and works. We investigate the nature of citing of authors, important journals and citing of works between them, journals preferred by authors and expose hierarchy of similar collaborating authors, based on keywords they use. We perform temporal analysis on one important journal as well. We give a comprehensive scientometric insight into the field of topological indices.

Application of graph theory in the library domain—Building a faceted framework based on a literature review

“…Moreover, document content from citation networks can be the basis for entity networks representing relationships for knowledge units such as drugs (Ding et al, 2013). As it is the case for citation (Kim and Barnett, 2008) and collaboration networks (Ding, 2011), keyword-based bibliometric analyses and social network analysis were also combined in multiple studies (Bodlaj and Batagelj, 2014; Hu et al, 2013; Su and Lee, 2010), for example, to create complex co-keyword networks and keywords co-occurrence networks (Cheng et al, 2018; Kastrin et al, 2014; Li et al, 2016). Yet recently, subject headings are still used separately for mapping science (Shu et al, 2017), to detect journal similarity (Yan and Chien, 2021) or in combination with co-citation and other metrics (Cabeza Ramrez et al, 2019).…”

Some Basic Results on the Second Multiplication Atom-Bond Connectivity Index

“…At present, in Iran, Pakistan and India, a large number of scholars use ISSN: 2456-8686, Volume 2, Issue 2, 2018:1-8 DOI : http://doi.org/10.26524/cm34 mathematical methods to study the properties of compounds. For the contributions on the topological index computation and its engineering applications one can refer to Balaban [1], Buscema et al [2], Gao et al [3,4,5], Bodlaj and Batagelj [6], Lokesha et al [7], Khakpoor and Keshe [8], and Ivanciuc [9]. This paper only covers simple (molecular) graphs.…”

Examining the literature on “Networks in Space and in Time.” An introduction

“…An overview of the papers' contents: ReferencesCitation analysis has a long tradition(Garfield et al, 1964) in comparing the impact and evolution of science in different fields (Lucio-Arias &Leydesdorff, 2008;Kejzar et al, 2010;Leydesdorff et al, 2011;Brughmans, 2013;Bodlaj & Batagelj, 2014). By counting the number of times a work has been cited by other works, it is able to map the seminal contributions that influenced the research tradition in a specific area, favoring scientific knowledge flow over time.In this perspective, a citation network could be considered a network in which social ties (direct connections) and cultural ties (indirect connections beyond the boundary of personal acquaintanceship) could appear(White, 2011).More formally, a citation network C is represented by a direct graph (acyclic network) defined by a collection of D documents (articles, working papers, books), or authors, where an arc going from the document d i to document d j is present if d i…”