The Scientific Collaboration Networks in University Management in Brazil

Abstract

The scientific collaboration, externalized through the formation of networks or research groups, has been used by researchers in the processes of production and publication of researches in the various areas of knowledge. On the basis of this, the aim of this article is to identify the structure of scientific collaboration networks in University Management among higher education institutions, based on the institutional links of researchers in this area. In terms of methodological steps, two data collections were done: one in the publications database of the Journal of University Management in Latin America (GUAL) to select the articles of interest in the research, and another in the current database of the Directory of Research Groups (DRG) of the National Council for Scientific and Technological Development (CNPq) to identify the research groups in University Management registered in the Directory. The main results evidenced the predominance of scientific collaboration in the production of research in the area and that the formation of networks is influenced by several factors, such as social aspects and professional aspirations of researchers, interests in sharing resources, as well as the geographical proximity of institutions.

Gravity-Law Based Critical Bots Identification in Large-Scale Heterogeneous Bot Infection Network

“…In recent years, critical nodes identification [20,21,[37][38][39][40][41][42] has been widely studied in complex networks. Typical identification methods include abstract distance [21], information entropy (IE) [38][39][40][41][42][43] and machine learning [29].…”

“…In recent years, critical nodes identification [20,21,[37][38][39][40][41][42] has been widely studied in complex networks. Typical identification methods include abstract distance [21], information entropy (IE) [38][39][40][41][42][43] and machine learning [29]. Shang et al [21] introduced effective distance to replace the Euclidean Distance for identifying influential nodes based on information fusion and multi-level processing.…”

Role-Aware Information Spread in Online Social Networks

“…Since these superspreader and influence nodes have a massive influence on a large population [31], numerous studies have tried to identify them. Classic examples include detecting influential researchers in a citation network [101]; understanding user communication patterns in email communication networks [102]; identifying important junctions in road networks that might create bottlenecks [103]; and analyzing critical stop locations of flights between airports [104]. These studies analyzed nodes' behavior to infer their informal (latent) social role, defined by the set of activities that users perform [105,106].…”

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“…The growing number of Latin American international SC research (Vanz and Stumpf, 2012) is often produced either with scientists from extra-regional countries or within national borders, as intra-regional SC has been found to be limited and, in some cases, restricted for countries with a small scientific development (Vanz and Stumpf, 2012;Stumpf et al, 2013;Munoz, Queupil and Fraser, 2016). Additionally, Latin American SC exhibits spatial heterogeneity patterns, as geographical proximity becomes critical, and most research occurs in specific cities within the countries, therefore remaining mostly local (Munoz, Queupil and Fraser, 2016;Sidone, Haddad and Mena-Chalco, 2017;Da Silva et al, 2018).…”