Bibliometric Maps of Science: The Visualization of Scientific Research

Bibliometric Maps of Science: The Visualization of Scientific Research

Irina Marshakova-Shaikevich (Adam Mickiewicz University, Poland)
DOI: 10.4018/978-1-5225-4990-1.ch008

Abstract

This chapter is devoted to directions in algorithmic classificatory procedures: co-citation analysis as an example of citation network and lexical analysis of keywords in the titles. The chapter gives the results of bibliometric analysis of the international scientific collaboration of EU countries. The three approaches are based on the same general idea of normalization of deviations of the observed data from the mathematical expectation. The application of the same formula leads to discovery of statistically significant links between objects (publication, journals, keywords, etc.) reflected in the maps. Material for this analysis is drawn from DBs presented in ISI Thomson Reuters (at present Clarivate Analytics).
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Introduction

The present chapter is devoted to direction in algorithmic classificatory procedures: co-citation analysis as an example of citation network and lexical analysis of keywords in the titles. The chapter will give the results of bibliometric analysis of the international scientific collaboration of EU countries. The five approaches are based on the same general idea of normalization of deviations of the observed data from the mathematical expectation. The application of the same formula leads to discovery of statistically significant links between objects (publication, journals, keywords, etc.) reflected in the maps.

This chapter includes five parts: (1) Co-citation maps of publications and authors, (2) Journal co-citation analysis , (3) bibliometric maps of the international scientific collaboration of EU countries, (4) the map of scientific organizations based on their thematic specters, (5) MEMORY and MEMORIES in lexical environment.

Material for this analysis is drawn from DBs presented in ISI Thomson Reuters (at present Clarivate Analytics)..

Since the beginning of the 1960-s a new direction in the study of science has been gaining ground – quantitative analysis of information flows. As is well known bibliometrics is one of the approaches to the study of science. Items of bibliometric analysis are publications grouped according to a multitude of aspects: journals, authors, countries, thematic fields, etc. The specific feature of bibliometrics is the use of secondary information: all kinds of bibliographic indexes: abstracts, and so on presented in various DBs The corresponding statistics may be of great interest for the analysts of science development, it may help in planning and management of science.

It is very important to underline two important sides of these directions of analysis should be mentioned at once.

  • 1.

    Bibliometrics is based on the huge amount of easily accessible secondary information well represented in various databases, particularly in the databases of the ISI (Thomson Reuters). It was exactly those databases that served as a starting point for the development of bibliometrics.

  • 2.

    Bibliometrics is primarily a quantitative study of the flow of documents. It is not aimed at finding a particular bit of information, it concentrates on discovering middle- and long-range trends, on strategic monitoring the development of science. The results are visualized in maps of science.

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Co-Citation Analysis Of Publications And Authors

The research in field of the science of science in the 1960-1970 was concentrated mainly in elaborating of synchronic classifications. The inclusion of time factor was one of the aims of present author in elaborating methods of prospective coupling. Two methods of automatic clustering were worked out, which could be applied to dynamic corpora of documents. The author’s further work in this direction was divided between 1) сo-citation analysis of publications and authors and 2) journal co-citation analysis (see part 2).

The present part of the chapter is based to the idea of co-citation as a tool of automatic classification of a set of items (a citation network). The method was worked out by the author from 1970 and was called ‘prospective coupling’ (Marshakova,1973) as contrasted to Kessler’s ‘bibliographic coupling’(Kessler, 1963).

From the mathematical point of view Citation network is a set of documents with the relation of citing imposed on it. In other words it is a union of a set of citing papers and a set of cited papers. A citation network is a potential base for various classifications of member-papers. Search for practical algorithmic (automatic) classification is a characteristic feature of present-day bibliometric analysis of citation networks. It was M. Kessler who in 1963 formulated the concept of 'bibliographic coupling' as a measure of similarity of two documents based on the number of common references. The method relies on past literature and may be called retrospective.

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