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This study investigates the interplay between online and face-to-face (FtF) feedback on stress during an important life event. We present data on a two-month, six-wave longitudinal study of 468 Chilean adolescents across three important stages of a competitive national university selection test (Prueba de Selección Universitaria [PSU]) to assess longitudinal and reciprocal relationships. Random intercept cross-lagged panel models (RI-CLPM) showed that online feedback had a small effect in decreasing stress during the three short-termed waves, before and after the three main events of the test: test taking, test scores, and final selection. No intrapersonal effects were found for FtF feedback on stress, and vice versa. At the interpersonal level, only feedback variables were related. Results suggest that prosocial replies on social media may slightly help to downregulate stress from important life events at the intrapersonal level, an effect which appears to be short-lived (e.g., only a few days), rather than long-lived (e.g., three weeks).

Science and technology develop not only along historical trajectories, but also as next-order regimes that periodically change the landscape. Regimes can incur on trajectories which are then disrupted. Using citations and references for the operationalization, we discuss and quantify both the recently proposed “disruption indicator” and the older indicator for “critical transitions” among reference lists as changes which may necessitate a rewriting of history. We elaborate this with three examples in order to provide a proof of concept. We shall show how the indicators can be calculated using Web-of-Science data. The routine is automated (available at < http://www.leydesdorff.net/software/di/index.htm >) so that it can be upscaled in future research. We suggest that “critical transitions” can be used to indicate disruption at the regime level, whereas disruption is developed at the trajectory level. Both conceptually and empirically, however, continuity is grasped more easily than disruption.

We propose the I3* indicator as a non-parametric alternative to the journal impact factor (JIF) and h-index. We apply I3* to more than 10,000 journals. The results can be compared with other journal metrics. I3* is a promising variant within the general scheme of non-parametric I3 indicators introduced previously: I3* provides a single metric which correlates with both impact in terms of citations (c) and output in terms of publications (p). We argue for weighting using four percentile classes: the top-1% and top-10% as excellence indicators; the top-50% and bottom-50% as output indicators. Like the h-index, which also incorporates both c and p, I3*-values are size-dependent; however, division of I3* by the number of publications (I3*/N) provides a size-independent indicator which correlates strongly with the 2- and 5-year journal impact factors (JIF2 and JIF5). Unlike the h-index, I3* correlates significantly with both the total number of citations and publications. The values of I3* and I3*/N can be statistically tested against the expectation or against one another using chi-squared tests or effect sizes. A template (in Excel) is provided online for relevant tests.

Scientific activity plays a major role in innovation for biomedicine and healthcare. For instance, fundamental research on disease pathologies and mechanisms can generate potential targets for drug therapy. This co-evolution is punctuated by papers which provide new perspectives and open new domains. Despite the relationship between scientific discovery and biomedical advancement, identifying these research milestones that truly impact biomedical innovation can be difficult and is largely based solely on the opinions of subject matter experts. Here, we consider whether a new class of citation algorithms that identify seminal scientific works in a field, Reference Publication Year Spectroscopy (RPYS) and multi-RPYS, can identify the connections between innovation (e.g., therapeutic treatments) and the foundational research underlying them. Specifically, we assess whether the results of these analytic techniques converge with expert opinions on research milestones driving biomedical innovation in the treatment of Basal Cell Carcinoma. Our results show that these algorithms successfully identify the majority of milestone papers detailed by experts (Wong and Dlugosz in J Investig Dermatol 134(e1):E18–E22, 2014)—thereby validating the power of these algorithms to converge on independent opinions of seminal scientific works derived by subject matter experts. These advances offer an opportunity to identify scientific activities enabling innovation in biomedicine.

International collaboration in science continues to grow at a remarkable rate, but little agreement exists about dynamics of growth and organization at the discipline level. Some suggest that disciplines differ in their collaborative tendencies, reflecting their epistemic culture. This study examines collaborative patterns in six previously studied specialties to add new data and analyze patterns over time. Our findings show that a global network of collaboration continues to add new nations and new participants; since 1990, each specialty has added many new nations to lists of collaborating partners. We also find that the scope of international collaboration is positively related to impact. Network characteristics for the six specialties are notable in that instead of reflecting underlying culture, they tend towards convergence at the global level. This observation suggests that the global level may represent next-order dynamics that feed back to the national and local levels (as subsystems) in a complex, networked hierarchy.

Twitter accounts have already been used in many scientometric studies, but the meaningfulness of the data for societal impact measurements in research evaluation has been questioned. Earlier research focused on social media counts and neglected the interactive nature of the data. We explore a new network approach based on Twitter data in which we compare author keywords to hashtags as indicators of topics. We analyze the topics of tweeted publications and compare them with the topics of all publications (tweeted and not tweeted). Our exploratory study is based on a comprehensive publication set of climate change research. We are interested in whether Twitter data are able to reveal topics of public discussions which can be separated from research-focused topics. We find that the most tweeted topics regarding climate change research focus on the consequences of climate change for humans. Twitter users are interested in climate change publications which forecast effects of a changing climate on the environment and to adaptation, mitigation and management issues rather than in the methodology of climate-change research and causes of climate change. Our results indicate that publications using scientific jargon are less likely to be tweeted than publications using more general keywords. Twitter networks seem to be able to visualize public discussions about specific topics., 31 pages, 1 table, and 7 figures

Using percentile shares, one can visualize and analyze the skewness in bibliometric data across disciplines and over time. The resulting figures can be intuitively interpreted and are more suitable for detailed analysis of the effects of independent and control variables on distributions than regression analysis. We show this by using percentile shares to analyze so-called “factors influencing citation impact” (FICs; e.g., the impact factor of the publishing journal) across years and disciplines. All articles (n = 2,961,789) covered by WoS in 1990 (n = 637,301), 2000 (n = 919,485), and 2010 (n = 1,405,003) are used. In 2010, nearly half of the citation impact is accounted for by the 10% most-frequently cited papers; the skewness is largest in the humanities (68.5% in the top-10% layer) and lowest in agricultural sciences (40.6%). The comparison of the effects of the different FICs (the number of cited references, number of authors, number of pages, and JIF) on citation impact shows that the JIF has indeed the strongest correlations with the citation scores. However, the correlation between FICs and citation impact is lower, if citations are normalized instead of using raw citation counts.

In their study entitled "Constructing bibliometric networks: A comparison between full and fractional counting," Perianes-Rodriguez, Waltman, & van Eck (2016; henceforth abbreviated as PWvE) provide arguments for the use of fractional counting at the network level as different from the level of publications. Whereas fractional counting in the latter case divides the credit among co-authors (countries, institutions, etc.), fractional counting at the network level can normalize the relative weights of links and thereby clarify the structures in the network. PWvE, however, propose a counting scheme for fractional counting that is one among other possible ones. Alternative schemes proposed by Batagelj and Cerin��ek (2013) and Park, Yoon, & Leydesdorff (2016; henceforth abbreviated as PYL) are discussed in an appendix. However, our approach is not correctly identified as identical to their Equation A3. Here below, we distinguish three approaches analytically; routines for applying these approaches to bibliometric data are also provided., accepted for publication in the Journal of Informetrics, 27 November 2016

Using co-authored publications between China and Korea in Web of Science (WoS) during the one-year period of 2014, we evaluate the government stimulation program for collaboration between China and Korea. In particular, we apply dual approaches, full integer vs. fractional counting, to collaborative publications in order to better examine both the patterns and contents of Sino-Korean collaboration networks in terms of individual countries and institutions. We first conduct a semi-automatic network analysis of Sino-Korean publications based on the full-integer counting method, and then compare our categorization with contextual rankings using the fractional technique; routines for fractional counting of WoS data are made available at http://www.leydesdorff.net/software/fraction . Increasing international collaboration leads paradoxically to lower numbers of publications and citations using fractional counting for performance measurement. However, integer counting is not an appropriate measure for the evaluation of the stimulation of collaborations. Both integer and fractional analytics can be used to identify important countries and institutions, but with other research questions., Comment: Accepted for publication in Scientometrics

We introduce a new tool - the CitedReferencesExplorer (CRExplorer, www.crexplorer.net) - which can be used to disambiguate and analyze the cited references (CRs) of a publication set downloaded from the Web of Science (WoS). The tool is especially suitable to identify those publications which have been frequently cited by the researchers in a field and thereby to study for example the historical roots of a research field or topic. CRExplorer simplifies the identification of key publications by enabling the user to work with both a graph for identifying most frequently cited reference publication years (RPYs) and the list of references for the RPYs which have been most frequently cited. A further focus of the program is on the standardization of CRs. It is a serious problem in bibliometrics that there are several variants of the same CR in the WoS. In this study, CRExplorer is used to study the CRs of all papers published in the Journal of Informetrics. The analyses focus on the most important papers published between 1980 and 1990., Comment: Accepted for publication in the Journal of Informetrics

Both “interdisciplinarity” and “synergy” are desirable features from a policy perspective: can surplus be found in the interactions among (disciplinary) bodies of knowledge? We have recently developed measures for “interdisciplinarity” and distinguished these measurements from those of “synergy.” In this study, we analyze three review papers by Judit Bar-Ilan (Scientometrics 50(1):7–32, 2001, Ann Rev Inf Sci Technol (ARIST) 38:231–288, 2004, J Informetr 2(1):1–52, 2008a) in terms of whether they rank high on interdisciplinarity and synergy values among the 130 papers of her œuvre. Review papers can be expected to fulfill a synergetic and perhaps also interdisciplinary function in scientific literature more than research articles, since the literature is considered from a broader perspective. Both the interdisciplinarity and synergy indicators point to Bar-Ilan (2004). The three reviews have high synergy scores. Whereas Bar-Ilan (2008a) contributed to the redefinition and shaping of the discipline of “information science,” Bar-Ilan (2004) added the broader perspective of the theoretical and practical relevance of the discipline. Bar-Ilan (2001) reviews various methods for data collection at the Internet. An article of Bar-Ilan and Peritz (2002) in Library Trends scores also high on synergy.

In a recent paper, Hirsch (hα: an index to quantify an individual’s scientific leadership, 2019. https://doi.org/10.1007/s11192-018-2994-1 ) proposes to attribute the credit for a co-authored paper to the α-author—the authors with the highest h-index—regardless of his or her actual contribution, effectively reducing the role of the other co-authors to zero. The indicator hα inherits most of the disadvantages of the h-index from which it is derived, but adds the normative element of reinforcing the Matthew effect in science. Using an example, we show that hα can be extremely unstable. The empirical attribution of credit among co-authors is not captured by abstract models such as h, $$\bar{h}$$ , or hα.

For the biomedical sciences, the Medical Subject Headings (MeSH) make available a rich feature which cannot currently be merged properly with widely used citing/cited data. Here, we provide methods and routines that make MeSH terms amenable to broader usage in the study of science indicators: using Web-of-Science (WoS) data, one can generate the matrix of citing versus cited documents; using PubMed/MEDLINE data, a matrix of the citing documents versus MeSH terms can be generated analogously. The two matrices can also be reorganized into a 2-mode matrix of MeSH terms versus cited references. Using the abbreviated journal names in the references, one can, for example, address the question whether MeSH terms can be used as an alternative to WoS Subject Categories for the purpose of normalizing citation data. We explore the applicability of the routines in the case of a research program about the amyloid cascade hypothesis in Alzheimer's disease (AD). One conclusion is that referenced journals provide archival structures, whereas MeSH terms indicate mainly variation (including novelty) at the research front. Furthermore, we explore the option of using the citing/cited matrix for main-path analysis as a by-product of the software., Comment: accepted for publication in Scientometrics, August 2016

CRExplorer version 1.6.7 was released on July 5, 2016. This version includes the following new features and improvements: Scopus: Using "File" - "Import" - "Scopus", CRExplorer reads files from Scopus. The file format "CSV" (including citations, abstracts and references) should be chosen in Scopus for downloading records. Export facilities: Using "File" - "Export" - "Scopus", CRExplorer exports files in the Scopus format. Using "File" - "Export" - "Web of Science", CRExplorer exports files in the Web of Science format. These files can be imported in other bibliometric programs (e.g. VOSviewer). Space bar: Select a specific cited reference in the cited references table, press the space bar, and all bibliographic details of the CR are shown. Internal file format: Using "File" - "Save", working files are saved in the internal file format "*.cre". The files include all data including matching results and manual matching corrections. The files can be opened by using "File" - "Open"., Accepted for publication in Scientometrics

Did the demise of the Soviet Union in 1991 influence the scientific performance of the researchers in Eastern European countries? Did this historical event affect international collaboration by researchers from the Eastern European countries with those of Western countries? Did it also change international collaboration among researchers from the Eastern European countries? Trying to answer these questions, this study aims to shed light on international collaboration by researchers from the Eastern European countries (Russia, Ukraine, Belarus, Moldova, Bulgaria, the Czech Republic, Hungary, Poland, Romania, and Slovakia). The number of publications and normalized citation impact values are compared for these countries based on InCites (Thomson Reuters), from 1981 up to 2011. The international collaboration by researchers affiliated to institutions in Eastern European countries at the time points of 1990, 2000 and 2011 was studied with the help of Pajek and VOSviewer software, based on data from the Science Citation Index (Thomson Reuters). Our results show that the breakdown of the communist regime did not lead, on average, to a huge improvement in the publication performance of the Eastern European countries and that the increase in international co-authorship relations by the researchers affiliated to institutions in these countries was smaller than expected. Most of the Eastern European countries are still subject to changes and are still awaiting their boost in scientific development.

In recent years, numerous studies have been published which have used bibliometric data to look at collaborations in research. This study presents a proposal with which the topical connections of the institutions of an organization can be investigated through analysis of co-authorships, direct citation links, and co-citations. Based on various bibliometric data sets for an organization whose institutions are used as an example, this study illustrates the possibility of comparing the self-perception of institutions of this organization (co-authorships, direct citation links) with a view to (possible) mutual collaboration with the external perception (co-citations). This comparison is made firstly for the whole organization with the aid of network graphs; secondly, the comparison is presented in a table for a specific institution and its (possible) collaborations in the organization. Particularly the tabular breakdown of the links between the institutions can provide concrete indications of possible further collaboration between the institutions which have not yet manifested themselves in co-authorships.

Augmented Reality (AR) enables consumers to virtually try products on their own face or surroundings in real time (e.g., make-up, furniture), which could help providing consumers a ‘try before you buy’ experience when shopping online. In an online experiment, we examined the potential positive and negative effects of online product presentation with AR, compared to two non-AR product presentations on a picture of the self or a model. Results suggest that AR enhances perceived informativeness and enjoyment of the shopping experience, as opposed to both non-AR product presentations. Consequently, perceived informativeness leads to a cognitive process which enhances purchase intention and willingness to share personal data with the brand, while perceived enjoyment leads to an affective process which enhances attitude towards the brand. At the same time, AR is perceived as more intrusive, but against expectations, this does not lead to any negative effects.

The percentages of shares of world publications of the European Union and its member states, China, and the United States have been represented differently as a result of using different databases. An analytical variant of the Web-of-Science (of Thomson Reuters) enables us to study the dynamics in the world publication system in terms of the field-normalized top-1% and top-10% most-frequently cited publications. Comparing the EU28, USA, and China at the global level shows a top-level dynamic that is different from the analysis in terms of shares of publications: the United States remains far more productive in the top-1% of all papers; China drops out of the competition for elite status; and the EU28 increased its share among the top-cited papers from 2000 to 2010. Some of the EU28 member states overtook the United States during this decade; but a clear divide remains between EU15 (Western Europe) and the Accession Countries. Network analysis shows that China was embedded in this top-layer of internationally co-authored publications. These publications often involve more than a single European nation.

Using the possible synergy among geographic, size, and technological distributions of firms in the Orbis database, we find the greatest reduction of uncertainty at the level of the 31 provinces of China, and an additional 18.0% at the national level. Some of the coastal provinces stand out as expected, but the metropolitan areas of Beijing and Shanghai are (with Tianjan and Chonqing) most pronounced at the next-lower administrative level of (339) prefectures, since these four metropoles are administratively defined at both levels. Focusing on high- and medium-tech manufacturing, a shift toward Beijing and Shanghai is indicated, and the synergy is on average enhanced (as expected; but not for all provinces). Unfortunately, the Orbis data is incomplete since it was collected for commercial and not for administrative or governmental purposes. However, we show a methodology that can be used by others who may have access to higher-quality statistical data for the measurement., Comment: accepted for publication in Scientometrics (October, 2013)

Percentile-based approaches have been proposed as a non-parametric alternative to parametric central-tendency statistics to normalize observed citation counts. Percentiles are based on an ordered set of citation counts in a reference set, whereby the fraction of papers at or below the citation counts of a focal paper is used as an indicator for its relative citation impact in the set. In this study, we pursue two related objectives: (1) although different percentile-based approaches have been developed, an approach is hitherto missing that satisfies a number of criteria such as scaling of the percentile ranks from zero (all other papers perform better) to 100 (all other papers perform worse), and solving the problem with tied citation ranks unambiguously. We introduce a new citation-rank approach having these properties, namely P100. (2) We compare the reliability of P100 empirically with other percentile-based approaches, such as the approaches developed by the SCImago group, the Centre for Science and Technology Studies (CWTS), and Thomson Reuters (InCites), using all papers published in 1980 in Thomson Reuters Web of Science (WoS). How accurately can the different approaches predict the long-term citation impact in 2010 (in year 31) using citation impact measured in previous time windows (years 1 to 30)? The comparison of the approaches shows that the method used by InCites overestimates citation impact (because of using the highest percentile rank when papers are assigned to more than a single subject category) whereas the SCImago indicator shows higher power in predicting the long-term citation impact on the basis of citation rates in early years. Since the results show a disadvantage in this predictive ability for P100 against the other approaches, there is still room for further improvements., Accepted for publication in the Journal of Informetrics

The Cooperative Patent Classifications (CPC) jointly developed by the European and US Patent Offices provide a new basis for mapping and portfolio analysis. This update provides an occasion for rethinking the parameter choices. The new maps are significantly different from previous ones, although this may not always be obvious on visual inspection. Since these maps are statistical constructs based on index terms, their quality--as different from utility--can only be controlled discursively. We provide nested maps online and a routine for portfolio overlays and further statistical analysis. We add a new tool for "difference maps" which is illustrated by comparing the portfolios of patents granted to Novartis and MSD in 2016., Scientometrics 112(3) (2017) 1573-1591; http://link.springer.com/article/10.1007/s11192-017-2449-0

One is inclined to conceptualize impact in terms of citations per publication, and thus as an average. However, citation distributions are skewed, and the average has the disadvantage that the number of publications is used in the denominator. Using hundred percentiles, one can integrate the normalized citation curve and develop an indicator that can be compared across document sets because percentile ranks are defined at the article level. I apply this indicator to the set of 58 journals in the ISI Subject Category of "Nanoscience & nanotechnology," and rank journals, countries, cities, and institutes using non-parametric statistics. The significance levels of results can thus be indicated. The results are first compared with the ISI-Impact Factors, but this Integrated Impact Indicator (I3) can be used with any set downloaded from the (Social) Science Citation Index. The software is made publicly available at the Internet. Visualization techniques are also specified for evaluation by positioning institutes on Google Map overlays., Scientometrics (in press). Paper to be presented at the 2011 Atlanta Conference on Science, Technology, and Innovation Policy, September 15-17, Atlanta GA

We use a trading metaphor to study knowledge transfer in the sciences as well as the social sciences. The metaphor comprises four dimensions: (a) Discipline Self-dependence, (b) Knowledge Exports/Imports, (c) Scientific Trading Dynamics, and (d) Scientific Trading Impact. This framework is applied to a dataset of 221 Web of Science subject categories. We find that: (i) the Scientific Trading Impact and Dynamics of materials science and transportation science have increased; (ii) biomedical disciplines, physics, and mathematics are significant knowledge exporters, as is statistics and probability; (iii) in the social sciences, economics, business, psychology, management, and sociology are important knowledge exporters; and (iv) Discipline Self-dependence is associated with specialized domains which have ties to professional practice (e.g., law, ophthalmology, dentistry, oral surgery and medicine, psychology, psychoanalysis, veterinary sciences, and nursing).

This paper examines the structural patterns of networks of internationally co-authored SCI papers in the domain of research driven by big data and provides an empirical analysis of semantic patterns of paper titles. The results based on data collected from the DVD version of the 2011 SCI database identify the U.S. as the most central country, followed by the U.K., Germany, France, Italy, Australia, the Netherlands, Canada, and Spain, in that order. However, some countries (e.g., Portugal) with low degree centrality occupied relatively central positions in terms of betweenness centrality. The results of the semantic network analysis suggest that internationally co-authored papers tend to focus on primary technologies, particularly in terms of programming and related database issues. The results show that a combination of words and locations can provide a richer representation of an emerging field of science than the sum of the two separate representations.

This article is distributed under the terms of the Creative Commons Attribution License., In August 2011, Thomson Reuters launched version 5 of the Science and Social Science Citation Index in the Web of Science (WoS). Among other things, the 222 ISI Subject Categories (SCs) for these two databases in version 4 of WoS were renamed and extended to 225 WoS Categories (WCs). A new set of 151 Subject Areas was added, but at a higher level of aggregation. Perhaps confusingly, these Subject Areas are now abbreviated “SC” in the download, whereas “WC” is used for WoS Categories. Since we previously used the ISI SCs as the baseline for a global map in Pajek (Pajek is freely available at http://vlado.fmf.uni-lj.si/pub/networks/pajek/) (Rafols et al., Journal of the American Society for Information Science and Technology 61:1871–1887, 2010) and brought this facility online (at http://www.leydesdorff.net/overlaytoolkit), we recalibrated this map for the new WC categories using the Journal Citation Reports 2010. In the new installation, the base maps can also be made using VOSviewer (VOSviewer is freely available at http://www.VOSviewer.com/) (Van Eck and Waltman, Scientometrics 84:523–538, 2010)., We acknowledge support from the ESRC grant RES-360-25-0076.

Percentiles have been established in bibliometrics as an important alternative to mean-based indicators for obtaining a normalized citation impact of publications. Percentiles have a number of advantages over standard bibliometric indicators used frequently: for example, their calculation is not based on the arithmetic mean which should not be used for skewed bibliometric data. This study describes the opportunities and limits and the advantages and disadvantages of using percentiles in bibliometrics. We also address problems in the calculation of percentiles and percentile rank classes for which there is not (yet) a satisfactory solution. It will be hard to compare the results of different percentile-based studies with each other unless it is clear that the studies were done with the same choices for percentile calculation and rank assignment.

The data of F1000 and InCites provide us with the unique opportunity to investigate the relationship between peers’ ratings and bibliometric metrics on a broad and comprehensive data set with high-quality ratings. F1000 is a post-publication peer review system of the biomedical literature. The comparison of metrics with peer evaluation has been widely acknowledged as a way of validating metrics. Based on the seven indicators offered by InCites, we analyzed the validity of raw citation counts (Times Cited, 2nd Generation Citations, and 2nd Generation Citations per Citing Document), normalized indicators (Journal Actual/Expected Citations, Category Actual/Expected Citations, and Percentile in Subject Area), and a journal based indicator (Journal Impact Factor). The data set consists of 125 papers published in 2008 and belonging to the subject category cell biology or immunology. As the results show, Percentile in Subject Area achieves the highest correlation with F1000 ratings; we can assert that for further three other indicators (Times Cited, 2nd Generation Citations, and Category Actual/Expected Citations) the “true” correlation with the ratings reaches at least a medium effect size.

When research groups are evaluated by an expert panel, it is an open question how one can determine the match between panel and research groups. In this paper, we outline two quantitative approaches that determine the cognitive distance between evaluators and evaluees, based on the journals they have published in. We use example data from four research evaluations carried out between 2009 and 2014 at the University of Antwerp.While the barycenter approach is based on a journal map, the similarity-adapted publication vector (SAPV) approach is based on the full journal similarity matrix. Both approaches determine an entity’s profile based on the journals in which it has published. Subsequently, we determine the Euclidean distance between the barycenter or SAPV profiles of two entities as an indicator of the cognitive distance between them. Using a bootstrapping approach, we determine confidence intervals for these distances. As such, the present article constitutes a refinement of a previous proposal that operates on the level of Web of Science subject categories.

Reference Publication Year Spectroscopy (RPYS) and Multi-RPYS provide algorithmic approaches to reconstructing the intellectual histories of scientific fields. With this brief communication, we describe a technical advancement for developing research historiographies by introducing RPYS i/o, an online tool for performing standard RPYS and Multi-RPYS analyses interactively (at http://comins.leydesdorff.net/). The tool enables users to explore seminal works underlying a research field and to plot the influence of these seminal works over time. This suite of visualizations offers the potential to analyze and visualize the myriad of temporal dynamics of scientific influence, such as citation classics, sleeping beauties and the dynamics of research fronts. We demonstrate the features of the tool by analyzing—as an example—the references in documents published in the journal Philosophy of Science.

A number of journal classification systems have been developed in bibliometrics since the launch of the Citation Indices by the Institute of Scientific Information (ISI) in the 1960s. These systems are used to normalize citation counts with respect to field-specific citation patterns. The best known system is the so-called "Web-of-Science Subject Categories" (WCs). In other systems papers are classified by algorithmic solutions. Using the Journal Citation Reports 2014 of the Science Citation Index and the Social Science Citation Index (n of journals = 11,149), we examine options for developing a new system based on journal classifications into subject categories using aggregated journal-journal citation data. Combining routines in VOSviewer and Pajek, a tree-like classification is developed. At each level one can generate a map of science for all the journals subsumed under a category. Nine major fields are distinguished at the top level. Further decomposition of the social sciences is pursued for the sake of example with a focus on journals in information science (LIS) and science studies (STS). The new classification system improves on alternative options by avoiding the problem of randomness in each run that has made algorithmic solutions hitherto irreproducible. Limitations of the new system are discussed (e.g. the classification of multi-disciplinary journals). The system's usefulness for field-normalization in bibliometrics should be explored in future studies., accepted for publication in the Journal of Informetrics, 20 July 2016

"Bibliometrics", "scientometrics", "informetrics", and "webometrics" can all be considered as manifestations of a single research area with similar objectives and methods, which we call "information metrics" or iMetrics. This study explores the cognitive and social distinctness of iMetrics with respect to the general information science (IS), focusing on a core of researchers, shared vocabulary and literature/knowledge base. Our analysis investigates the similarities and differences between four document sets. The document sets are drawn from three core journals for iMetrics research (Scientometrics, Journal of the American Society for Information Science and Technology, and Journal of Informetrics). We split JASIST into document sets containing iMetrics and general IS articles. The volume of publications in this representation of the specialty has increased rapidly during the last decade. A core of researchers that predominantly focus on iMetrics topics can thus be identified. This core group has developed a shared vocabulary as exhibited in high similarity of title words and one that shares a knowledge base. The research front of this field moves faster than the research front of information science in general, bringing it closer to Price's dream., Accepted for publication in Scientometrics

During the last decade, we have witnessed a sustained growth of South Korea’s research output in terms of the world share of publications in the Science Citation Index database. However, Korea’s citation performance is not yet as competitive as publication performance. In this study, the authors examine the intellectual structure of Korean S&T field based on social network analysis of journal-journal citation data using the ten Korean SCI journals as seed journals. The results reveal that Korean SCI journals function more like publication places, neither research channels nor information sources among national scientists. Thus, these journals may provide Korean scholars with access to international scientific communities by facilitating the respective entry barriers. However, there are no citation relations based on their Korean background. Furthermore, we intend to draw some policy implications which may be helpful to increase Korea’s research potential.

Socio-cognitive action reproduces and changes both social and cognitive structures. The analytical distinction between these dimensions of structure provides us with richer models of scientific development. In this study, I assume that (i) social structures organize expectations into belief structures that can be attributed to individuals and communities; (ii) expectations are specified in scholarly literature; and (iii) intellectually the sciences (disciplines, specialties) tend to self-organize as systems of rationalized expectations. Whereas social organizations remain localized, academic writings can circulate, and expectations can be stabilized and globalized using symbolically generalized codes of communication. The intellectual restructuring, however, remains latent as a second-order dynamics that can be accessed by participants only reflexively. Yet, the emerging "horizons of meaning" provide feedback to the historically developing organizations by constraining the possible future states as boundary conditions. I propose to model these possible future states using incursive and hyper-incursive equations from the computation of anticipatory systems. Simulations of these equations enable us to visualize the couplings among the historical--i.e., recursive--progression of social structures along trajectories, the evolutionary--i.e., hyper-incursive--development of systems of expectations at the regime level, and the incursive instantiations of expectations in actions, organizations, and texts., accepted for publication in Scientometrics (June 2015)

Dyads of journals related by citations can agglomerate into specialties through the mechanism of triadic closure. Using the Journal Citation Reports 2011, 2012, and 2013, we analyze triad formation as indicators of integration (specialty growth) and disintegration (restructuring). The strongest integration is found among the large journals that report on studies in different scientific specialties, such as PLoS ONE, Nature Communications, Nature, and Science. This tendency towards large-scale integration has not yet stabilized. Using the Islands algorithm, we also distinguish 51 local maxima of integration. We zoom into the cited articles that carry the integration for: (i) a new development within high-energy physics and (ii) an emerging interface between the journals Applied Mathematical Modeling and the International Journal of Advanced Manufacturing Technology. In the first case, integration is brought about by a specific communication reaching across specialty boundaries, whereas in the second, the dyad of journals indicates an emerging interface between specialties. These results suggest that integration picks up substantive developments at the specialty level. An advantage of the bottom-up method is that no ex ante classification of journals is assumed in the dynamic analysis., Accepted for publication in Journal of Informetrics

The dynamics of innovation are nonlinear and complex: geographical, technological, and economic selection environments can be expected to interact. Can patents provide an analytical lens to this process in terms of different attributes such as inventor addresses, classification codes, backward and forward citations, etc.? Two recently developed patent maps with interactive overlay techniques--Google Maps and maps based on citation relations among International Patent Classifications (IPC)--are elaborated into dynamic versions that allow for online animations and comparisons by using split screens. Various forms of animation are explored. The recently developed Cooperative Patent Classifications (CPC) of the U.S. Patent and Trade Office (USPTO) and the European Patent Office (EPO) provide new options for a precise delineation of samples in both USPTO data and the Worldwide Patent Statistics Database (PatStat) of EPO. Among the "technologies for the mitigation of climate change" (class Y02), we zoom in on nine material technologies for photovoltaic cells; and focus on one of them (CuInSe2) as a lead case. The longitudinal development of Rao-Stirling diversity in the IPC-based maps provides a heuristics for studying technological generations during the period under study (1975-2012). The sequencing of generations prevails in USPTO data more than in PatStat data because PatStat aggregates patent information from countries in different stages of technological development, whereas one can expect USPTO patents to be competitive at the technological edge., Comment: accepted for publication in Scientometrics on September 10, 2014

The findings of Bornmann, Leydesdorff, and Wang (in press) revealed that the consideration of journal impact improves the prediction of long-term citation impact. This paper further explores the possibility of improving citation impact measurements on the base of a short citation window by the consideration of journal impact and other variables, such as the number of authors, the number of cited references, and the number of pages. The dataset contains 475,391 journal papers published in 1980 and indexed in Web of Science (WoS, Thomson Reuters), and all annual citation counts (from 1980 to 2010) for these papers. As an indicator of citation impact, we used percentiles of citations calculated using the approach of Hazen (1914). Our results show that citation impact measurement can really be improved: If factors generally influencing citation impact are considered in the statistical analysis, the explained variance in the long-term citation impact can be much increased. However, this increase is only visible when using the years shortly after publication but not when using later years., Comment: Accepted for publication in the Journal of Informetrics. arXiv admin note: text overlap with arXiv:1306.4454

Recent discussion about the increase in international research collaboration suggests a comprehensive global network centred around a group of core countries and driven by generic socio-economic factors where the global system influences all national and institutional outcomes. In counterpoint, we demonstrate that the collaboration pattern for countries in Africa is far from universal. Instead, it exhibits layers of internal clusters and external links that are explained not by monotypic global influences but by regional geography and, perhaps even more strongly, by history, culture and language. Analysis of these bottom-up, subjective, human factors is required in order to provide the fuller explanation useful for policy and management purposes., Comment: 12 pp, 5 Figs including map links to viewer

Trabajo presentado a la 18th International Conference on Science and Technology Indicators: "Translational twists and turns: Science as a socio-economic endeavor" celebrada en Berlín (Alemania) del 4 al 6 de Septiembre de 2013., We report on the development of an interface to the US Patent and Trademark Office (USPTO) that allows for the mapping of patent portfolios as overlays to basemaps constructed from citation relations among all patents contained in this database during the period 1976–2011. Both the interface and the data are in the public domain; the freeware programs VOSViewer and/or Pajek can be used for the visualization. These basemaps and overlays can be generated at the 3-digit and/or 4-digit levels of the International Patent Classifications (IPC) of the World Intellectual Property Organization (WIPO). The basemaps provide a stable mental framework for analysts to follow developments over searches for different years, which can be animated. The full flexibility of the advanced search engines of USPTO are available for generating sets of patents and/or patent applications which can thus be visualized and compared. This instrument allows for addressing questions about technological distance, diversity in portfolios, and animating the developments of both technologies and technological capacities of organizations over time. Rao-Stirling diversity measures are provided on the basis of “technological distances” (Jaffe, 1989:88), that is, (1 — cosine)., We acknowledge support by the ESRC project ‘Mapping the Dynamics of Emergent Technologies’ (RES-360-25-0076).

Using (binomial) regression analysis, we run models using citation windows of one to ten years with both annual citation and cumulative citations as dependent variables, and with both bibliometric and quality indicators (judgments of peers) as independent variables. The bibliometric variables are the journal impact factor (JIF) of the publication medium, the numbers of authors and pages, and the statistical citedness of the references used within the paper. We find that the JIF have a larger influence on the citation impact of a publication than the quality (measured by judgments of peers). However, the number of pages and the quality of the references are less influential. The influence of JIF peaks after three years and then declines (in most regression analyses), but remains higher than the influence of quality judgments even after ten years. These results call into question a discrepancy between the algorithmically based indicators and the qualitative judgments by experts. The latter seems less predictive for future citation than a combination of algorithmic constructs. The results of this study can contribute to the empirical specification of the relevance of a normative versus a constructivist theory of citation.

Mutual information in three (or more) dimensions can be considered as a Triple-Helix indicator of synergy in university-industry-government relations. An open-source routine th4.exe makes the computation of this indicator interactively available at the Internet, and thus applicable to large sets of data. Th4.exe computes all probabilistic entropies and mutual information in two, three, and, if available in the data, four dimensions among, for example, classes such as geographical addresses (cities, regions), technological codes (e.g., OECD's NACE codes), and size categories; or, alternatively, among institutional addresses (academic, industrial, public sector) in document sets. The relations between the Triple-Helix indicator -- as an indicator of synergy -- and the Triple-Helix model that specifies the possibility of feedback by an overlay of communications, are also discussed., submitted to a special issue of Scientometrics entitled "Mapping Triple Helix Innovation for Developing and Transitional Economies: Webometrics, Scientometrics, and Informetrics"

A Triple Helix (TH) network of bi- and trilateral relations among universities, industries, and governments can be considered as an ecosystem in which uncertainty can be reduced when functions become synergetic. The functions are based on correlations among distributions of relations, and therefore latent. The correlations span a vector space in which two vectors (P and Q) can be used to represent forward "sending" and reflexive "receiving," respectively. These two vectors can also be understood in terms of the generation versus reduction of uncertainty in the communication field that results from interactions among the three bi-lateral channels of communication. We specify a system of Lotka---Volterra equations between the vectors that can be solved. Redundancy generation can then be simulated and the results can be decomposed in terms of the TH components. Furthermore, we show that the strength and frequency of the relations are independent parameters in the model. Redundancy generation in TH arrangements can be decomposed using Fourier analysis of the time-series of empirical studies. As an example, the case of co-authorship relations in Japan is re-analyzed. The model allows us to interpret the sinusoidal functions of the Fourier analysis as representing redundancies.

We have developed a (freeware) routine for "referenced publication years spectroscopy" (RPYS) and apply this method to the historiography of "iMetrics," that is, the junction of the journals Scientometrics, Informetrics, and the relevant subset of JASIST (approx. 20%) that shapes the intellectual space for the development of information metrics (bibliometrics, scientometrics, informetrics, and webometrics). The application to information metrics (our own field of research) provides us with the opportunity to validate this methodology, and to add a reflection about using citations for the historical reconstruction. The results show that the field is rooted in individual contributions of the 1920s-1950s (e.g., Alfred J. Lotka), and was then shaped intellectually in the early 1960s by a confluence of the history of science (Derek de Solla Price), documentation (e.g., Michael M. Kessler's "bibliographic coupling"), and "citation indexing" (Eugene Garfield). Institutional development at the interfaces between science studies and information science has been reinforced by the new journal Informetrics since 2007. In a concluding reflection, we return to the question of how the historiography of science using algorithmic means--in terms of citation practices--can be different from an intellectual history of the field based, for example, on reading source materials., Comment: Journal of Informetrics, accepted for publication (20 Nov. 2013)

The gap in statistics between multi-variate and time-series analysis can be bridged by using entropy statistics and recent developments in multi-dimensional scaling. For explaining the evolution of the sciences as non-linear dynamics, the configurations among variables can be important in addition to the statistics of individual variables and trend lines. Animations enable us to combine multiple perspectives (based on configurations of variables) and to visualize path-dependencies in terms of trajectories and regimes. Path-dependent transitions and systems formation can be tested using entropy statistics., Scientometrics, in press (Nov. 2012)

In "Caveats for using statistical significance tests in research assessments,"--Journal of Informetrics 7(1)(2013) 50-62, available at arXiv:1112.2516 -- Schneider (2013) focuses on Opthof & Leydesdorff (2010) as an example of the misuse of statistics in the social sciences. However, our conclusions are theoretical since they are not dependent on the use of one statistics or another. We agree with Schneider insofar as he proposes to develop further statistical instruments (such as effect sizes). Schneider (2013), however, argues on meta-theoretical grounds against the specification of uncertainty because, in his opinion, the presence of statistics would legitimate decision-making. We disagree: uncertainty can also be used for opening a debate. Scientometric results in which error bars are suppressed for meta-theoretical reasons should not be trusted.

The modified SNIP indicator of Elsevier, as recently explained by Waltman et al. (2013) in this journal, solves some of the problems which Leydesdorff & Opthof (2010 and 2011) indicated in relation to the original SNIP indicator (Moed, 2010 and 2011). The use of an arithmetic average, however, remains unfortunate in the case of scientometric distributions because these can be extremely skewed (Seglen, 1992 and 1997). The new indicator cannot (or hardly) be reproduced independently when used for evaluation purposes, and remains in this sense opaque from the perspective of evaluated units and scholars., Letter to the Editor of the Journal of Informetrics (2013; in press)

Bibliometric indicators such as journal impact factors,h-indices, and total citation counts are algorithmic artifacts that can be used in research evaluation and management. These artifacts have no meaning by themselves, but receive their meaning from attributions in institutional practices. We distinguish four main stakeholders in these practices: (1) producers of bibliometric data and indicators; (2) bibliometricians who develop and test indicators; (3) research managers who apply the indicators; and (4) the scientists being evaluated with potentially competing career interests. These different positions may lead to different and sometimes conflicting perspectives on the meaning and value of the indicators. The indicators can thus be considered as boundary objects which are socially constructed in translations among these perspectives. This paper proposes an analytical clarification by listing an informed set of (sometimes unsolved) problems in bibliometrics which can also shed light on the tension between simple but invalid indicators that are widely used (e.g., theh-index) and more sophisticated indicators that are not used or cannot be used in evaluation practices because they are not transparent for users, cannot be calculated, or are difficult to interpret.