The claim that co-citation analysis is a useful tool to map subject-matter specialties of scientific research in a given period, is examined. A method has been developed using quantitative analysis of content-words related to publications in order to: (1) study coherence of research topics within sets of publications citing clusters, i.e., (part of) the "current work" of a specialty; (2) to study differences in research topics between sets of publications citing different clusters; and (3) to evaluate recall of "current work" publications concerning the specialties identified by co-citation analysis. Empirical support is found for the claim that co-citation analysis identifies indeed subject-matter specialties. However, different clusters may identify the same specialty, and results are far from complete concerning the identified "current work." These results are in accordance with the opinion of some experts in the fields. Low recall of co-citation analysis concerning the "current work" of specialties is shown to be related to the way in which researchers build their work on earlier publications: the "missed" publications equally build on very recent earlier work, but are less "consensual" and/or less "attentive" in their referencing practice. Evaluation of national research performance using co-citation analysis appears to be biased by this "incompleteness."
Combined analysis of co-citation relations and words is explored to study time-dependent ("dynamical") aspects of scientific activities, as expressed in research publications. This approach, using words originating from publications citing documents in co-citation clusters, offers an additional and complementary possibility to identify and link specialty literature through time, compared to the exclusive use of citations. Analysis of co-citation relations is used to locate and link groups of publications that share a consensus concerning intellectual base literature. Analysis of word-profile similarity is used to identify and link publication groups that belong to the same subject-matter research specialty. Different types of "content-words" are analyzed, including indexing terms, classification codes, and words from title and abstract of publications. The developed methods and techniques are illustrated using data of a specialty in atomic and molecular physics. For this specialty, it is shown that, over a period of 10 years, continuity in intellectual base was at a lower level than continuity in topics of current research. This finding indicates that a series of interesting new contributions are made in course of time, without vast alteration in general topics of research. However, within this framework, a more detailed analysis based on timeplots of individual cited key-articles and of content-words reveals a change from more rapid succession of new empirical studies to more retrospective, and theoretically oriented studies in later years. IntroductionCombined analysis of co-citation relations and wordprofile similarities is explored to improve the capability of quantitative techniques to depict structural and dynamical aspects of scientific research. In our foregoingThis study is part of a project financed by the Ministry of Education and Sciences, through the Netherlands Advisory Council for Science Policy (RAWB).Received February 24, 1989; revised October 4, 1989; accepted October 10, 1989. 0 1991 publication ("Mapping I," Braam et al., this issue) we emphasize the structural aspects ("local stability") of "science mapping," while in this article we focus on the analysis of dynamical aspects ("temporal stability") of scientific research.Starting with a clustering of documents that often co-occur in the reference lists of publications (cocitation clustering), publications in the dataset are grouped on the base of (one or more) citations to these clustered documents. This "classification" of publications is believed to partition the dataset according to participation of publications in research specialties Griffith et al., 1974;Small, 1977;Small & Crane, 1979). The prevalent idea that the "current research" publications of specialties are identified in this way, is based on theories of Price (1965) and Kuhn (1970). In particular the way researchers draw on earlier work, and their sharing of a set of "exemplars" (or "paradigm"), is considered to be reflected in the referencing practices of specialty members....
In this study we have measured word-profile similarities between citing and cited publications, as well as between publications citing specific highly cited papers. This "cognitive resemblance" was operationalized by different similarity measures using various kinds of terms and classification types. This study focuses on publications of internationally recognized chemical engineering scientists for the year 1982 as "source" publications, and subsequent publications (of other scientists) citing to these publications. This study empirically shows that publications with a citation relationship are significantly more content-related than other publications. It also shows that highly cited documents are mainly cited within their own research area. Thus, at least in chemical engineering, publications sharing citations to the same highly cited article, represent work of the same subject-matter research area. This is certainly not caused by the "narrowness" of the field, as we also show that there is a clear distribution of publications over many (sub)fields so that chemical engineering can be characterized as a broad, interdisciplinary research field. A weak relationship between word-profiles and type of classification was found, and this relationship differs between various types of classification.Mapping based on correspondence analysis clearly visualizes content-related groups of citing and cited publications. Our findings are contrary to the results of some earlier studies and to opinions in circles of sociologists of science that authors refer to publications in a rather arbitrary way mainly for adornment of their claims. These differences can be explained simply with statistical arguments.
In this study some novel indicators and publication data resources are explored to study the dynamics of genomics research at three different levels: worldwide; national and at individual Research Centers. Our results indicate that the growth of genomics research worldwide seems to be stabilizing, whereas genomics research in the Netherlands aims at getting 'ready for the next step'. As we find differences in research dynamics at the level of individual Research Centers, governmental support in a 'next step' could take these differences into account. For this purpose, we introduce a general model of research dynamics and timing of research management, building on ideas of Price and Bonaccorsi. Based on this model a framework is presented to discuss steering options in relation to research dynamics. We apply this framework to Research Centers of the Netherlands Genomics Initiative (NGI) and discuss findings.
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