2018
DOI: 10.3389/frma.2018.00004
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Mapping Affinities in Academic Organizations

Abstract: Scholarly affinities are one of the most fundamental hidden dynamics that drive scientific development. Some affinities are actual, and consequently can be measured through classical academic metrics such as co-authoring. Other affinities are potential, and therefore do not leave visible traces in information systems; for instance, some peers may share interests without actually knowing it. This article illustrates the development of a map of affinities for academic collectives, designed to be relevant to thre… Show more

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Cited by 7 publications
(4 citation statements)
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References 22 publications
(15 reference statements)
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“…These initial layers fade out by zooming in, leaving room for more specific information such as nodes and close keywords (Fig. 4), hosted in the hexagonal tiling [25]. Furthermore, moving over one researcher with the cursor reveals their tokens and coauthors.…”
Section: Operating Instructionsmentioning
confidence: 99%
“…These initial layers fade out by zooming in, leaving room for more specific information such as nodes and close keywords (Fig. 4), hosted in the hexagonal tiling [25]. Furthermore, moving over one researcher with the cursor reveals their tokens and coauthors.…”
Section: Operating Instructionsmentioning
confidence: 99%
“…Although simplicity is a great quality to properly address messages through visuals, the incredible work of Albert-László Barabási and his peers at Northeastern University supports alternative paths led to exploring innovative ways to present network diagrams (Rodighiero et al, 2018). This text aims to discuss the problem of scalability that severely affects networks that are characterized by millions or even billions of nodes and edges, producing what is commonly known as the spaghetti effect (Börner, 2015;Venturini, 2011).…”
Section: Removing Linksmentioning
confidence: 99%
“…The origin of centrality stays in the concept of being the "star" of a social group, which is being popular and worthy of attention. But in network analysis, centrality also determines the node's relevancy [15]. Such a measure can be mathematically calculated but also diagrammatically interpreted, as in networks it is rather easy to see whether a node is central or not.…”
Section: The Issue Of Network Centralitymentioning
confidence: 99%