Exploring the Co-Authorship Network Among Cnpq’s Productivity Fellows in the Area of Industrial Engineering

Andrade, Ricardo Lopes de; Rêgo, Leandro Chaves

doi:10.1590/0101-7438.2017.037.02.0277

Cited by 9 publications

(5 citation statements)

References 21 publications

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“…The network is undirected and the edges' weights represent the number of publications made in coauthorship by a given pair of researchers in the period of 2005 to 2014. (Andrade and Rêgo, 2017). (ii) Trade of American Countries: The network of commerce between American countries is formed by 30 countries and 356 edges.…”

Section: Datamentioning

confidence: 99%

A proposal for the EI index for fuzzy groups

Andrade

Rêgo

2022

Soft Comput

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In this paper, it is proposed a measure that quantifies the relational structure within and between groups that comprehend not only the analysis of disjoint groups or non-disjoint groups but also in fuzzy groups. This measure is based on the existing measure known as the EI index. The current EI index is a measure of homophily applied to networks with the presence of disjoint groups, although disjoint groups on a large scale rarely exist in many empirical networks. The new measure permits the expansion of the analysis of social networks, for several types of attributes, and thus generating previously untapped knowledge. Moreover, it is also proposed combining edges' and nodes' weights in the evaluation of the EI index. The new measure is tested in two networks in different contexts. The first one is a co-authorship network, where researchers, actors in the network, are divided according to the time of completion of the doctorate. The second network is formed by trade relations between countries of the American continent, where countries are grouped according to the Human Development Index.

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Section: Datamentioning

confidence: 99%

A proposal for the EI index for fuzzy groups

Andrade

Rêgo

2022

Soft Comput

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“…Eigenvector is another micro-level metrics of centrality used to analyze the co-authorship network and identify the influence of an author within the network. An author, which is connected to many other co-authors that are themselves well-connected, has a high eigenvector centrality and an author connected to few co-authors who also have a few connections has a much lower score [65]. Thus, in the representation in Figure 4 the nodes were sized in respect to the value of the of the eigenvector centrality of each author and co-author in the network structure.…”

Section: Top 10 Authorsmentioning

confidence: 99%

“…(0.47) were ranked first, as those two authors shared many co-authors, while Soylak M. (0.40) followed, as he exceeded the rest of the authors, demonstrating high number of both publications and CI, as noted in Table 5's data. The collaboration network of the top 10 authors had (i) a graph density [65] of 0.014, meaning that only 1.4% of the possible connections in the network occurred and (ii) an average degree [65] of 2, meaning that only two, on average, authors were connected in the network As a result, such analysis can provide the basis for the possibility to optimize collaboration between main and non-mainstream authors, and to strengthen and tighten the existing collaborations, so as to build a stronger network in the future [66].…”

Section: Top 10 Authorsmentioning

confidence: 99%

Nano-Adsorbents for Cobalt Removal from Wastewater: A Bibliometric Analysis of Research Articles Indexed in the Scopus Database

Prochaska

Gallios

2021

Processes

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In this study, a combined technique of bibliometric and social network analysis was applied on research articles, related to the application of nano-adsorbents for cobalt removal from wastewater, published in Scopus database up to 2020. The results revealed that the first relative research article appeared in the Scopus database in the year 2002. The total output of research articles reached 214 in the year 2020. Published research articles of the years 2014–2020, added up to 83.6% of total articles. King Saud University of Saudi Arabia, Chinese Academy of Science, and LUT University of Finland were found to serve as the gatekeepers who control information flows in the network of the most prolific institutions, while cooperation between China, Saudi Arabia, and United States was also identified. On average, the most prolific authors cooperated with five others, while the top 10 cited publications appeared to represent a sparse and weakly interconnected network of co-authors. Graphene oxide was the most prominent nano-adsorbent among the top 10 cited publications, and their respective co-citations network visualization helped in capturing the value of certain citations to the evolution of the research on the topic, putting thus scientific work impact assessment to a different perspective.

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“…The goal of this comparison is to see how our network performs compared to other networks. Table 1 presents a comparison between CAN and 4 other co-authorship networks, namely, ACM, Biology, and Physics networks [11], and Engineering network [18]. According to the aforementioned table, the C value of CAN reflected a weak tendency of authors to collaborate.…”

Section: Co-authorship Networkmentioning

confidence: 99%

Measuring scientific collaboration in co-authorship networks

Mahmood

Sultan

Thanoon

et al. 2021

IJ-AI

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<span lang="EN-US">Scientific research is currently considered one of the key factors in the development of our life. It plays a significant role in managing our business, study, and work more conveniently. One of the important aspects when it comes to scientific research is the level of collaboration among researchers/disciplines. The collaboration between two different disciplines contributes to obtaining more reliable solutions for our everyday issues. Therefore, it is needed to understand the collaboration patterns among researchers and come up with convenient strategies for strengthening this kind of collaboration. In this work, we aim at investigating the patterns of scientific collaboration among researchers across disciplines. To this end, we generate a co-authorship network for several disciplines. The generated network reveals many interesting facts regarding the collaboration patterns among researchers who work in the same/different disciplines. We involve several measurements in this study that evaluate different aspects, which is of interest to the research communities since most of the studies in the literature measure specific aspects. Moreover, we propose a novel metric for measuring scientific collaboration in a research community and use it to benchmark the collaboration among disciplines. Finally, we use the obtained results/facts in providing recommendations for scientific communities.</span>

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Exploring the Co-Authorship Network Among Cnpq’s Productivity Fellows in the Area of Industrial Engineering

Cited by 9 publications

References 21 publications

A proposal for the EI index for fuzzy groups

A proposal for the EI index for fuzzy groups

Nano-Adsorbents for Cobalt Removal from Wastewater: A Bibliometric Analysis of Research Articles Indexed in the Scopus Database

Measuring scientific collaboration in co-authorship networks

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