1 A Comparison of Two Techniques for Bibliometric (original) (raw)
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A comparison of two techniques for bibliometric mapping: Multidimensional scaling and VOS
Journal of the American Society for Information Science and Technology, 2010
VOS is a new mapping technique that can serve as an alternative to the wellknown technique of multidimensional scaling. We present an extensive comparison between the use of multidimensional scaling and the use of VOS for constructing bibliometric maps. In our theoretical analysis, we show the mathematical relation between the two techniques. In our experimental analysis, we use the techniques for constructing maps of authors, journals, and keywords. Two commonly used approaches to bibliometric mapping, both based on multidimensional scaling, turn out to produce maps that suffer from artifacts. Maps constructed using VOS turn out not to have this problem. We conclude that in general maps constructed using VOS provide a more satisfactory representation of a data set than maps constructed using well-known multidimensional scaling approaches.
… ISKO Conference, 25-29 August 1998 …, 1998
This paper shows that, given co-citation data, Kohonen feature mapping produces results quite similar to those of multidimensional scaling, the traditional mode for computer-assisted mapping of intellectual domains. It further presents a Kohonen feature map based on author co-citation data that links author names to information about them on the World Wide Web. The results bear on a goal for present-day information science: the integration of computerized bibliometrics with document retrieval. 1. Introduction Literature mapping, a form of domain analysis that uses spatial metaphors to show relationships between articles, oeuvres, or journals, has a pedigree at least 30 years old. Through those years, literature maps have appeared on paper with all the static qualities of print. Now, however, one may see them as stages in the evolution of designs for an interactive computer interface. The maps, which have high summarizing power, are potential interfaces for the automated retrieval of documents to which they are linked (White & McCain, 1998a). Two computer-assisted modes for visualizing literatures are cluster-augmented multidimensional scaling and Kohonen feature maps. This paper compares the output of the two graphical techniques when they are used with similar input data. The data are drawn from White and McCain (l998b), which mapped the discipline of information science in terms of its most highly cited authors during the period 1972-1995. White and McCain (1998b) typifies author co-citation analysis (ACA) as it has been practiced since the original work of White and Griffith (1981). This paper contrasts classic ACA, employing multidimensional scaling, with a Kohoncn feature map made by Xia Lin from the same set of authors. When Lin joined White and McCain on the faculty of Drexel University'S College of Information Science and Technology in 1997, they provided him with their co-cited author data for reuse. Lin's (1998) Website, viewable with a Java-equipped browser and described below, is the outcome. Properly can-ied out, ACA has shown itself to yield highly intelligible results, but it is labor-intensive and time-consuming to do. The attraction of Kohonen mapping is that it conveys much of the information of MDS, but is faster and somewhat easier to adapt as an interface for further computerized processes, such as linking to the Websites of selected authors or retrieval of documents by them. The White and McCain baseline study mapped the top 120 authors of information science in two-dimensional subject space. The raw data were counts of the times that works by any two authors in the top 120 were jointly cited in later Writings. (One must have been cited in well over 100 articles at minimum to qualify.) The counts were obtained by systematic ANDing of cited-author pairs in a large-scale retrieval from Social Scisearch on DIALOG. Such counts fonn profiles (hat can be summarized by correlation coefficients (Pearson r's) between each pair of oeuvres (for example, Miranda Lee Pao's and Jean Tague
Software survey: VOSviewer, a computer program for bibliometric mapping
Scientometrics, 2010
We present VOSviewer, a freely available computer program that we have developed for constructing and viewing bibliometric maps. Unlike most computer programs that are used for bibliometric mapping, VOSviewer pays special attention to the graphical representation of bibliometric maps. The functionality of VOSviewer is especially useful for displaying large bibliometric maps in an easy-to-interpret way. The paper consists of three parts. In the first part, an overview of VOSviewer’s functionality for displaying bibliometric maps is provided. In the second part, the technical implementation of specific parts of the program is discussed. Finally, in the third part, 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.
A comparison of mapping algorithms for author co-citation data analysis
Proceedings of the American Society for Information Science and Technology, 2010
A key process of any citation analysis study is to map the coded citation data from a high-dimensional dataset to a lower dimensional one while detecting the groups, clusters, patterns or other features of the citation relationships. Over the years, many methods have been used in various studies, including multi-dimensional scaling, Pathfinder networks, Kohonen's self-organizing mapping, etc. Many of these methods are fundamentally different, but their results are similar and comparable. In this study, we selected and applied four of the mapping methods to the same dataset, the author co-citation matrix of the top 100 highly cited information scientists. The results of the different mapping methods provide interesting comparisons among the different mapping algorithms as well as the different views of the dataset.
2006
The visualization of scientific field structures is a classic of scientometric studies. This paper presents a domain analysis of the library and information science discipline based on author co-citation analysis (ACA) and journal co-citation analysis (JCA). The techniques used for map con-struction are the self-organizing map (SOM) neural algorithm, Ward’s clustering method and multidimensional scaling (MDS). The results of this study are compared with similar research developed by Howard White and Katherine McCain [1]. The methodologies used allow us to confirm that the subject domains identified in this paper are, as well, present in our study for the corresponding period. The appearance of studies pertaining to library science reveals the relationship of this realm with information science. Especially significant is the presence of the management on the journal maps. From a methodological standpoint, mean-while, we would agree with those authors who consider MDS, the SOM and clu...
Adding Perspective to the Bibliometric Mapping Using Bidirected Graph
Open Information Science, 2023
Bibliometric mapping offers easiness in analyzing the relationship between publications through the network visuals created. Several applications, such as VOSviewer, Bibliometrix, and CiteSpace, make conducting network analysis more convenient. Moreover, the relationship provided is usually in the form of an undirected graph, which negates the two-way relationship created. This study attempts to demonstrate the significance of considering two-way relationships by proposing a keyword network formed using bidirected graphs and association rules to examine the two-way relationship of two or more keywords. According to the proposed bidirected graph, a twoway graph can add value and insight by analyzing the correlation between a single keyword and several others. Two of the four metrics used, Confidence and Conviction, are sufficient to support directed graphs. In contrast, Support and Full Counting are related because they both see the occurrences of a keyword, so using undirected graphs is necessary.
Journal of advancement in Library Science, 2019
In the fastest growing technological world of information and communication technology, scientific research and development, an overwhelming amount of information / data in various formats is generated directly or indirectly. As far as academic and scientific community is concerned, a large number of scholarly articles are being published on daily basis by research scholars and academician across the world. After the introduction of Computer Technology computerized data processing has become common among the researchers, this has been prompted to develop Bibliometric software. Some of them are open source software (Freeware) and others are commercial products. The study comprises to assess the potential value of data analysis of selected open source Bibliometric and Scientometric Packages (Tools).
A unified approach to mapping and clustering of bibliometric networks
Journal of Informetrics, 2010
In the analysis of bibliometric networks, researchers often use mapping and clustering techniques in a combined fashion. Typically, however, mapping and clustering techniques that are used together rely on very different ideas and assumptions. We propose a unified approach to mapping and clustering of bibliometric networks. We show that the VOS mapping technique and a weighted and parameterized variant of modularity-based clustering can both be derived from the same underlying principle. We illustrate our proposed approach by producing a combined mapping and clustering of the most frequently cited publications that appeared in the field of information science in the period 1999-2008.
On the use of biplot analysis for multivariate bibliometric and scientific indicators
Journal of the American Society for Information Science and Technology, 2013
Bibliometric mapping and visualization techniques represent one of the main pillars in the field of scientometrics. Traditionally, the main methodologies employed for representing data are Multi-Dimensional Scaling, Principal Component Analysis or Correspondence Analysis. In this paper we aim at presenting a visualization methodology known as Biplot analysis for representing bibliometric and science and technology indicators. A Biplot is a graphical representation of multivariate data, where the elements of a data matrix are represented according to dots and vectors associated with the rows and columns of the matrix. In this paper we explore the possibilities of applying the Biplot analysis in the research policy area. More specifically we will first describe and introduce the reader to this methodology and secondly, we will analyze its strengths and weaknesses through three different study cases: countries, universities and scientific fields. For this, we use a Biplot analysis known as JK-Biplot. Finally we compare the Biplot representation with other multivariate analysis techniques. We conclude that Biplot analysis could be a useful technique in scientometrics when studying multivariate data and an easy-to-read tool for research decision makers.
Word bibliographic coupling: Another way to map science field and identify core references
Proceedings of the Association for Information Science and Technology, 2019
This study investigates how to measure subject relationship based on bibliographic coupling strength. Since the 1960s, researchers use citation analysis methods to discover the relationship between different works and authors. However, how to apply citation-based methods in measuring the relationships between various subjects remains unknown. We propose a novel method to measure relationships between subjects based on bibliographic coupling strengths. Our dataset is composed of 7,692 articles published in 10 core information science journals from 2008 to 2017. The result shows that our method provides another viewpoint of exploring the development of science. Furthermore, our method can identify the core works in different subjects and help to judge how similar different subjects are.