Scientometric indicators and their exploitation by journal publishers Name: Pranay Parsuram Student number: 2240564 Course: Master’s Thesis (Book and Digital Media Studies) Supervisor: Prof. Fleur Praal Second reader: Dr. Adriaan van der Weel Date of completion: 12 July 2019 Word count: 18177 words 1 Contents 1. Introduction ............................................................................................................................ 3 2. Scientometric Indicators ........................................................................................................ 8 2.1. Journal Impact Factor ...................................................................................................... 8 2.2. h-Index .......................................................................................................................... 10 2.3. Eigenfactor™ ................................................................................................................ 11 2.4. SCImago Journal Rank.................................................................................................. 13 2.5. Source Normalized Impact Per Paper ........................................................................... 14 2.6. CiteScore ....................................................................................................................... 15 2.6. General Limitations of Citation Count .......................................................................... 16 3. Conceptual Framework ........................................................................................................ 18 3.1. Academic Publishing..................................................................................................... 18 3.2. Academic Journal Publishing ........................................................................................ 21 3.2.1. Researcher Considerations ..................................................................................... 23 4. Scientometric Indicators and Journal Publishers ................................................................. 27 4.1. Use of Scientometric Indicators .................................................................................... 27 4.1.1. Journal Pricing ........................................................................................................ 28 4.2. Manipulation of Scientometric Indicators ..................................................................... 32 4.2.1. Article Type ............................................................................................................ 32 4.2.2. Co-authorship and Subject Area ............................................................................. 33 4.2.3. Manipulation of Citable Items ................................................................................ 35 4.2.4. Self-citation ............................................................................................................ 36 4.2.5. Accessibility ........................................................................................................... 37 4.3. Alternative to Scientometric Indicators......................................................................... 43 4.4. Open Science ................................................................................................................. 45 5. Conclusion ........................................................................................................................... 47 Bibliography ............................................................................................................................ 50 2 1. Introduction The emergence of the Web has shown considerable promise as a means to transform academic communication.1 This is because the Web offers academics and various research institutions to ‘publish, annotate, review, discover and make links between research outputs’.2 Given these affordances, governments and funding agencies in many countries are now able to get directly involved in systematically evaluating the scientific outputs of universities and research institutions and their research productivity and quality. This systematic evaluation aids with providing measures to improve the performance of a given institution and provides a basis for decision-making about the allocation of research funding. The major means for determining the overall scientific output of an institution is scientometrics.3 In this thesis, I will shed light on how journal publishers exploit and manipulate this dependence of universities and research institutions on scientometrics for their own commercial interests. This chapter of the thesis provides a brief introduction of scientometrics and its use in the context of my research question. Until around 1970, research regarding the growth and development of academic and, in particular, scientific knowledge, was considered to be a philosophical field. More emphasis was laid on the validity of knowledge. However, the question regarding how this knowledge was being produced was not focused on. The latter question was considered to belong to the realm of the social sciences.4 Then, in 1969, the term scientometrics was coined in Russia. This term was intended to examine all aspects of the literature of science and technology. By 1978, the term had attained wide recognition because of the establishment of a journal called Scientometrics in Hungary.5 This journal is still in publication today, and it deals with ‘the quantitative features and characteristics of science and scientific research’.6 Furthermore, Tague-Sutcliffe provides a simple definition of scientometrics as follows: ‘Scientometrics is the study of the quantitative aspects of science as a discipline or economic activity.’7 1 J. Stewart, R. Procter, R. Williams & M. Poschen, ‘The role of academic publishers in shaping the development of Web 2.0 services for scholarly communication’, New Media & Society, 15:3 (2013), p. 414. 2 Ibid., p. 414. 3 D. Pontille & D. Torny, ‘The controversial policies of journal ratings: Evaluating social sciences and humanities’, Research Evaluation, 19:5 (2010), pp. 347–348. 4 L. Leydesdorff, The challenge of scientometrics: The development, measurement, and self-organization of scientific communications, (Universal Publishers, 2011), p. 15. 5 W. Hood & C. Wilson, ‘The literature of bibliometrics, scientometrics, and informetrics’, Scientometrics, 52:2 (2001), p. 293. 6 Anon., ‘Description’, Scientometrics <https://link.springer.com/journal/11192> (10 June 2019). 7 J. Tague-Sutcliffe, ‘An introduction to informetrics’, Information Processing & Management, 28:1 (1992), p. 1. 3 Scientometrics is related to and has overlapping fields with bibliometrics.8 Bibliometrics has been in use in different forms for over a century or more. However, the term was officially coined only in 1969,9 around the same time as scientometrics. The major difference between bibliometrics and scientometrics is that the former mainly focuses on the quantitative aspects of the literature of science and scholarship, whereas the latter considers the literature as well as other aspects of science and technology, such as researcher practices, socio-organizational structures, research and development management and governmental regulations.10 Inherently, both concepts are used as a tool to measure research output in the form of publications, and as such, the terms have been used inconsistently and inter- changeably in existing literature. However, as scientometrics is a broader concept, it fits better in the context of this thesis; therefore, I will be using this term throughout. The two basic metrics involved in scientometrics are the number of publications and the number of citations that these publications receive. These metrics can be evaluated at different levels and for different objects such as a single publication, a researcher, a researcher unit, an institution or a country.11 Conventional scientometrics only provides raw data about the publication and citation count, which is generally derived from databases such as Web of Science, Scopus, PubMed, Google Scholar and others. To interpret this data, more sophisticated indicators have been implemented, for example, journal impact factor (IF), h- index, field normalized citation indicators, Eigenfactor™ (EF), SCImago journal rank (SJR), source normalised impact per paper (SNIP) and CiteScore. The reason for the introduction of these indicators is that publication and citation trends differ by disciplines and even sub- disciplines. Therefore, more objective and normalized indicators are required for comparisons between disciplines.12 One of the first scientometric indicators was the IF,13 and it was proposed in the 1950s.14 Since then, scientometric indicators have gradually become one of the main means for characterisation of research evolution.15 Scientometric indicators are an effective means of determining the evolution of research in a given field and can hence help 8 Hood & Wilson, ‘The literature of bibliometrics’, p. 291. 9 Ibid., p. 292. 10 Ibid., pp. 293–294. 11 J. Wilsdon, J. Bar-Ilan, R. Frodeman, E. Lex, I. Peters & P.F. Wouters, ‘Next-generation metrics: Responsible metrics and evaluation for open science,’ Report of the European Commission Expert Group on Altmetrics, (2017), <https://openaccess.leidenuniv.nl/bitstream/handle/1887/58254/report.pdf?> (10 June 2019), p. 8. 12 Ibid., p. 9. 13 J.C. Oosthuizen & J.E. Fenton, ‘Alternatives to the impact factor’, The