A connectionist and multivariate approach to science maps: the SOM, clustering and MDS applied to library and information science research

Abstract

Abstract.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 cocitation analysis (JCA). The techniques used for map construction 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, meanwhile, we would agree with those authors who consider MDS, the SOM and clustering as complementary methods that provide representations of the same reality from different analytical points of view. Even so, the MDS representation is the one offering greater possibilities for the structural representation of the clusters in a set of variables.Keywords: domain analysis; author co-citation analysis (ACA); journal co-citation analysis (JCA); library and information science; multidimensional scaling (MDS); self-organizing map (SOM) IntroductionThe perception and representation of reality are complicated undertakings. Tufte [2] expressed it well with these words: '. . . the world is complex, dynamic, multidimensional; paper is static, flat. How are we to represent the rich visual world of experience and measurement on mere flatland?' The visualization of information is an activity that humans have developed over time in a two-dimensional form, conditioned by the restrictions of the traditional document forms [3]. The arrival of the digital computer meant a brave new tool for processing, visualizing and analysing information structures that could not be comprehended outside a computerized context. Williams [4] White and McCain [5] introduce the problem of the visualization of literatures, stating, 'The trend now is to combine computerized graphics -visualizations -with computerized document retrieval, thereby making literatures seem more responsive.' This would represent the convergence of the two main lines of information science (IS) research into a single area, that of the visualization of the specialized literature of the discipline. The first of these lines of research comprises informetric-bibliometric studies, and is also known as the domain analysis [6]; the second would be that of information retrieval [7,8].Thus, we find ourselves with two clearly differentiated functions -analysis and interface -which we must attempt to integrate by introducing the methodology of visualization. There is, however, a gap between the two spheres. This gap has been described, though not resolved, by several author...

Mapping Evaluation for Semantic Browsing

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Biobibliometric profiling: An examination of multifaceted approaches to scholarship

“…Identifying an equal number of male and female coevals was not easy. We found that "most-cited" lists of information science researchers (e.g., Moya-Anegon, Herrero-Solana, & Jimenez-Contreras, 2006;White, 2003) Table 1.…”

Expansion of scientific journal categories using reference analysis: How can it be done and does it make a difference?

“…Pioneering work on grouping of journals into subject categories based on reference/citation analysis was carried out by PINSKY & NARIN [1976]. An alternative way to group journals is journal co-citation analysis, based on the number of times any pair of journals is cited in the same source article (e.g., [MOYA-ANEGON & AL., 2006].…”