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Open AccessJournal ArticleDOI

A unified approach to mapping and clustering of bibliometric networks

Ludo Waltman, +2 more
- 01 Oct 2010 - 
- Vol. 4, Iss: 4, pp 629-635
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TLDR
In this paper, a unified approach to mapping and clustering of bibliometric networks is proposed, where the VOS mapping technique and a weighted and parameterized variant of modularity-based clustering can both be derived from the same underlying principle.
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This article is published in Journal of Informetrics.The article was published on 2010-10-01 and is currently open access. It has received 1158 citations till now. The article focuses on the topics: Cluster analysis.

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Citations
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Journal ArticleDOI

bibliometrix: An R-tool for comprehensive science mapping analysis

TL;DR: This paper proposes a unique open-source tool, designed by the authors, called bibliometrix, for performing comprehensive science mapping analysis, programmed in R, and can be rapidly upgraded and integrated with other statistical R-packages.
Journal ArticleDOI

Science mapping software tools: Review, analysis, and cooperative study among tools

TL;DR: The aim of this article is to review, analyze, and compare some of the software tools used to carry out science mapping analysis, taking into account aspects such as the bibliometric techniques available and the different kinds of analysis.
Book ChapterDOI

Visualizing Bibliometric Networks

TL;DR: This chapter provides an introduction to the topic of visualizing bibliometric networks and focuses specifically on two software tools: VOSviewer and CitNetExplorer.
Journal ArticleDOI

TRY plant trait database : Enhanced coverage and open access

Jens Kattge, +754 more
TL;DR: The extent of the trait data compiled in TRY is evaluated and emerging patterns of data coverage and representativeness are analyzed to conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements.
Journal ArticleDOI

Citation-based clustering of publications using CitNetExplorer and VOSviewer

TL;DR: Using the approach presented in this paper, bibliometricians are able to carry out sophisticated cluster analyses without the need to have a deep knowledge of clustering techniques and without requiring advanced computer skills.
References
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Journal ArticleDOI

Finding and evaluating community structure in networks.

TL;DR: It is demonstrated that the algorithms proposed are highly effective at discovering community structure in both computer-generated and real-world network data, and can be used to shed light on the sometimes dauntingly complex structure of networked systems.
Journal ArticleDOI

Community detection in graphs

TL;DR: A thorough exposition of the main elements of the clustering problem can be found in this paper, with a special focus on techniques designed by statistical physicists, from the discussion of crucial issues like the significance of clustering and how methods should be tested and compared against each other, to the description of applications to real networks.
Journal ArticleDOI

Software survey: VOSviewer, a computer program for bibliometric mapping.

TL;DR: VOSviewer’s ability to handle large maps is demonstrated by using the program to construct and display a co-citation map of 5,000 major scientific journals.
Journal ArticleDOI

Graph drawing by force-directed placement

TL;DR: A modification of the spring‐embedder model of Eades for drawing undirected graphs with straight edges is presented, developed in analogy to forces in natural systems, for a simple, elegant, conceptually‐intuitive, and efficient algorithm.
Journal ArticleDOI

Fast algorithm for detecting community structure in networks.

TL;DR: An algorithm is described which gives excellent results when tested on both computer-generated and real-world networks and is much faster, typically thousands of times faster, than previous algorithms.
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