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The Challenge of Scientometrics THE CHALLENGE OF SCIENTOMETRICS THE DEVELOPMENT, MEASUREMENT, AND SELF-ORGANIZATION OF SCIENTIFIC COMMUNICATIONS Cognitions Texts Authors Loet Leydesdorff Copyright © Loet Leydesdorff, 2001 All rights reserved. The Challenge of Scientometrics: The Development, Measurement, and Self-Organization of Scientific Communications Loet Leydesdorff. – uPUBLISH.COM: Universal Publishers. Includes bibliographical references and index. Subject headings: self-organization, information sciences, communication theory, science studies, knowledge, scientometrics, indicators First published by DSWO Press, Leiden University Leiden, The Netherlands, 1995 Second edition. Published by Universal Publishers / uPUBLISH.com USA • 2001 ISBN: 1-58112-681-6 http://www.upublish.com/books/leydesdorff-sci.htm To learn more about this book visit the home page of the author at http://www.leydesdorff.net/ TABLE OF CONTENTS 1 Scientometrics and Science Studies 1 1.1 The challenge of scientometrics 3 1.2 Words, co-words, information, entropy, self- organization 5 1.3 Organization of the study 6 PART ITHEORETICAL PERSPECTIVES ON SCIENTOMETRICS 2 Scientometrics and the Sociology of Scientific Knowledge 15 2.1 Units of analysis, levels of aggregation, and dimensions 17 2.2 The sociology of scientific knowledge (SSK) 18 2.2.1 The delineation of the unit of analysis 22 2.2.2 Whitley’s (1984) solution 24 2.3 Discourse analysis 27 2.4 The sociology of translation 28 2.5 Networks of actors / Networks of words 31 2.6 Conclusions 33 3 The Intellectual Organization of the Sciences 37 3.1 Knowledge and language in the (neo-)conventionalist tradition 39 3.2 The epistemological priority of scientific methods 40 i 3.3 Scientific method as a function of scientific discourse 43 3.4 The social sciences 44 3.5 From disciplinary axiomata to organized sciences 47 3.5.1 Multi-, inter-, and trans-disciplinarity 49 3.5.2 The analytical character of dimensions 51 3.6 Conclusions 52 4 The Methodological Priority of Textual Data 57 4.1 The network model of scientific theories 57 4.2 Texts and co-occurrences of words 59 4.2.1 Levels of aggregation in scientific texts 61 4.2.2 Units of analysis 65 4.3 Full text analysis of a single document in terms of words 68 4.3.1 Word structures at different levels of aggregation 73 4.3.2 The attribution of sentences to sections 78 4.4 Conclusions 82 5 Full Text Analysis of Scientific Articles 85 5.1 Sample choice 87 5.2 Processing 93 5.3 Results 93 5.4 Conclusions 97 5.5 Consequences for building artificial intelligence using lexicon 98 6 From Words and Co-Words to Information and Probabilistic Entropy 101 6.1 What is indicated by the indicators? 101 6.2 Theories and methods in science studies 103 6.3 Methodological requirements in science studies 104 6.4 Summary and Conclusions 108 ii PART II METHODOLOGICAL STUDIES USING INFORMATION THEORY 7 The Static Model 111 7.1 The information measure 111 7.2 Sample choice 114 7.3 Results 115 7.3.1 Relations between articles and the set 115 7.3.2 Dimensions of the transmission 116 7.4 Generalization for three dimensions 120 7.5 The aggregation problem 124 7.6 Which words? 127 7.7 Conclusions 129 8 Modeling the Dynamics of Scientific Developments 131 8.1 Methods 132 8.2 Changes in distributions of word occurrences among texts 135 8.3 The problem of emergence 140 8.4 Publications as events in the field of Dictyostelium discoideum 143 8.4.1 Normalization in terms of an a posteriori event 144 8.4.2 Normalization across texts 146 8.4.3 Critical revisions in the sectional dimensions 151 8.5 Towards the generation of expert systems from scientific texts 155 9 The Static and Dynamic Analysis of Network Data 159 9.1 ‘Citing’ and ‘cited’ as variables in a static design 162 9.2 Cluster analysis 163 9.2.1 Agglomerative clustering 163 9.2.2 Divisive clustering 166 9.2.3 Confirmational usage 172 9.3 Graphs and cliques 173 9.4 The dynamic analysis 178 9.4.1 Changing patterns 178 iii 9.4.2 The dynamics of relations among the thirteen journals 180 9.5 Revision of the prediction 184 9.6 Forecasting 185 9.7 Summary and conclusions 190 9.8 Relevance for social network analysis 191 10 Irreversibilities in Science and Technology Networks 195 10.1 Methodology 196 10.2 Markov chains and the problem of ‘emergence’ 206 10.3 Conclusions 210 10.4 Applications 212 10.4.1 Auto-amplification and probabilistic scenario building 212 10.4.2 Co-evolution models and innovation studies 215 10.4.3 Implications for firm behaviour and institutional agency 220 PART III COMMUNICATION, PROBABILISTIC ENTROPY, AND SELF-ORGANIZATION 225 11 The Impact of EU Policies on the Transnational Publication System 229 11.1 The measurement of publication performance 230 11.2 Distributions and systems 237 11.2.1 Does the EC develop as a single publication system? 239 11.2.2 Between member-state co-authorships 242 11.2.3 Extension to the period 1988-1991 244 11.3 From “whether?” towards “when?” and “why?” 245 11.4 Has a system of co-authorship relations emerged? 248 11.5 Conclusions and discussion 249 iv 12 Knowledge Representations, Bayesian Inferences, and Empirical Science Studies 253 12.1 Information theoretical evaluation of Bayes’ formula 253 12.2 Application to social network analysis 255 12.3 An empirical example in scientometrics 258 12.4 Bayesian reasoning 262 12.4.1 Bayesian philosophy of science 262 12.4.2 The use of the Bayesian theorem in artificial intelligence 264 12.4.3 The decomposition of the a posteriori state in terms of the a priori one (The Quine-Duhem Thesis) 266 12.4.4 The evidencing of the evidence 269 12.5 Expert systems in science and science studies 270 12.5.1 The frame problem 271 12.5.2 Genesis and validity 273 13 The Possibility of a Mathematical Sociology of Scientific Communications 277 13.1 Uncertainty, information, and sociological meaning 278 13.2 The recursivity of communication 282 13.3 The empirical delineation of communication systems 285 13.4 The hypothetical status of communication systems 288 13.5 Methodological and theoretical conclusions 292 13.5.1 Methodological conclusions 292 13.5.2 Theoretical conclusions 294 13.6 Relevance for the Sociology of Scientific Knowledge 300 13.7 Relevance for the Sociology of Translation and Co-word Analysis 306 13.8 The further challenge of Scientometrics 310 v List of original publications 314 Bibliography 316 Author Index 335 Subject Index 338 vi PREFACE This study is the result of several years of collaboration as a scientometrician with philosophers, historians, and sociologists of science. It goes without saying that I am grateful to my colleagues in the Department of Science & Technology Dynamics of the University of Amsterdam for their relentless criticism and scepticism about scientometrics. In 1987, I had the opportunity to organize a workshop on the relations between qualitative theories in science and technology studies and the use of scientometric methods under the aegis of the European Association of Studies in Science and Technology (EASST), and to help edit a special issue of Scientometrics devoted to this subject (see: Leydesdorff et al. 1989). The program of study in this book is largely based on the research agenda that was formulated during this workshop. Among the many colleagues, with whom I have discussed issues relevant to this study, I am particularly grateful to Susan Cozzens for several years of collaboration, and to Michel Callon and Jean-Pierre Courtial for discussions about the co-word methodology. In 1990, I spent some time as their guest at the Centre de Sociologie de l’Innovation of the École Nationale Supérieure des Mines in Paris. In the Dutch context, I wish to mention my colleagues Gertrud Blauwhof, Peter Van den Besselaar (Department of Social Science Informatics), Wouter Van Rossum (Groningen State University), and Arie Rip (Twente University) for discussions of scientometric methods and their theoretical interpretation. Finally, I am indebted to Gene Moore for correcting my English, but I remain responsible for any mistakes in the text. Amsterdam, February 1995 vii Preface to the second edition This second edition is not substantially different from the first one published by DSWO Press (Leiden University) in 1995. The text has been thoroughly revised, updated, and improved as necessary. I am grateful to Manfred Bonitz for spotting a number of errors and typos in the first edition. Among other things, I extended Chapter Ten with a new section about the implications of path- dependent transitions for firm behaviour and institutional agency (Blauwhof 1995; Leydesdorff and Van den Besselaar 1998). The first edition has in the meantime been translated into Japanese by Yuko Fujigaki, Takayuki Hayashi, Hideyuki Hirakawa, Junichiro Makino, Masahi Shirabe, and Hiroyuki Tomizawa under the title Saientometorikus no chôsen: kagaku-gijyutsu-joho no jiko- soshiki-ka (Tokyo: Tamagawa University Press, 2001). The discussions with my Japanese colleagues were particularly intensive during the preparation of a special issue of Scientometrics on the ‘Theory of Citations,’ (Vol. 34, No. 1; see Leydesdorff 1998). In this context, I would also like to thank my colleague Paul Wouters for his contribution to what he has called The Citation Culture (Wouters 1999; Leydesdorff and Wouters 1999). A further elaboration of my theory is available in A Sociological Theory of Communications: The Self-Organization of the Knowledge-Based Society (Universal Publishers, at http://www.upublish.com/books/leydesdorff.htm, 2001). The two books can be considered complementary in terms of providing theory and methods for the investigation of the knowledge base in processes of scientific communication and codification.
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