Personal Research Database

Full Text: 2011\Scientometrics88, 213.pdf

Abstract: Patents constitute an up-to-date source of competitive intelligence in technological development, thus, patent analysis has been a vital tool for identifying technological trends. Patent citation analysis is easy to use, but fundamentally has two main limitations: (1) new patents tend to be less cited than old ones and may miss citations to contemporary patents, (2) citation-based analysis cannot be used for patents in databases which do not require citations. Naturally, citation-based analysis tends to underestimate the importance of new patents and may not work in rapidly-evolving industries in which technology life-cycles are shortening and new inventions are increasingly patented worldwide. As a remedy, this paper proposes a patent network based on semantic patent analysis using subject-action-object (SAO) structures. SAO structures represent the explicit relationships among components used in a patent, and are considered to represent key concepts of the patent or the expertise of the inventor. Based on the internal similarities between patents, the patent network provides the up-to-date status of a given technology. Furthermore, this paper suggests new indices to identify the technological importance of patents, the characteristics of patent clusters, and the technological capabilities of competitors. The proposed method is illustrated using patents related to synthesis of carbon nanotubes. We expect that the proposed procedure and analysis will be incorporated into technology planning processes to assist experts such as researchers and R&D policy makers in rapidly-evolving industries.

Keywords: Bibliometrics, Citation, Citation Analysis, Citation Network, Citations, Databases, Development, Diffusion, Indicators, Natural Language Processing (NLP), Natural-Language, Opportunities, Patent, Patent Mining, Patent Network, Patents, Policy, Research and Development (R&D) Trend, Semantic Patent Similarity, Similarity, Small World, Subject-Action-Object (SAO) Structures

? Abramo, G., D’Angelo, C.A. and Di Costa, F. (2011), National research assessment exercises: The effects of changing the rules of the game during the game. Scientometrics, 88 (1), 229-238.

Full Text: 2011\Scientometrics88, 229.pdf

Abstract: National research evaluation exercises provide a comparative measure of research performance of the nation’s institutions, and as such represent a tool for stimulating research productivity, particularly if the results are used to inform selective funding by government. While a school of thought welcomes frequent changes in evaluation criteria in order to prevent the subjects evaluated from adopting opportunistic behaviors, it is evident that the “rules of the game” should above all be functional towards policy objectives, and therefore be known with adequate forewarning prior to the evaluation period. Otherwise, the risk is that policy-makers will find themselves faced by a dilemma: should they reward universities that responded best to the criteria in effect at the outset of the observation period or those that result as best according to rules that emerged during or after the observation period? This study verifies if and to what extent some universities are penalized instead of rewarded for good behavior, in pursuit of the objectives of the “known” rules of the game, by comparing the research performances of Italian universities for the period of the nation’s next evaluation exercise (2004-2008): first as measured according to criteria available at the outset of the period and next according to those announced at the end of the period.

Keywords: Assessment, Bibliometric Indicators, Bibliometrics, Evaluation, Evaluation Criteria, Italy, Performance-Based Research Funding, Policy, Research, Research Assessment Exercises, Research Evaluation, Research Performance, Universities, University

? Breschi, S. and Malerba, F. (2011), Assessing the scientific and technological output of EU Framework Programmes: Evidence from the FP6 projects in the ICT field. Scientometrics, 88 (1), 239-257.

Full Text: 2011\Scientometrics88, 239.pdf

Abstract: This paper provides a quantitative assessment of the scientific and technological productivity of FP6 projects by exploiting a new database on articles and patents resulting from EU funded projects. Starting from the FP6, the design of the European technology policy has undergone significant changes with the introduction of new funding instruments aimed at achieving a “critical mass” of resources. Our empirical results provide support to the concerns, expressed by several observers, regarding the fact that the new funding instruments may have resulted in artificially “too large” research consortia. The available empirical evidence shows that scientific productivity increases with the number of participants following a U-inverted shape, thereby indicating the existence of decreasing marginal returns to an increase in the size of research consortia. A second key result of the paper is related to the existence of significant differences of performance among funding instruments. In particular, after accounting for the larger amount of resources allocated to them, Integrated Projects perform less well in terms of scientific output than both STRePs and Networks of Excellence and they do not exhibit a superior performance than STRePs in terms of patent applications.

Keywords: Assessment, Bibliometric Analysis, Framework Programme, Patent, Policy, Research, Research Consortia, Scientific And Technological Performance

? Choi, D.G., Lee, H. and Sung, T.K. (2011), Research profiling for ‘standardization and innovation’. Scientometrics, 88 (1), 259-278.

Full Text: 2011\Scientometrics88, 259.pdf

Abstract: This paper addresses the profiling of research papers on ‘standardization and innovation’-exploring major topics and arguments in this field. Drawing on 528 papers retrieved from the database, Web of Science, we employed trend, factor, and clustering analyses to demonstrate that the standardization and innovation research has continuously grown from publication of 13 papers in 1995 to 68 papers in 2008, the majority of these papers have been published in the six subject group domains of management, economics, environment, chemistry, computer science, and telecommunications. Technology innovation management specialty journals are the most central sources favorable for these themes. We also present an exploratory taxonomy that offers nine topical clusters to demonstrate the contextual structures of standardization and innovation. The implications of our results for ongoing consistent policy and future research into standardization and innovation are discussed.

Keywords: Bibliometrics, Clustering Analysis, Dominant Designs, Economics, Empirical-Analysis, Environment, Industry Standards, Information-Systems, Innovation, Intellectual Property-Rights, Journals, Papers, Performance, Policy, Publication, Publication Analysis, Quality Standards, Research, Research Papers, Research Profiling, Science-and-Technology, Setting Organizations, Standardization, Taxonomy, Technical Innovations, Trend, Web of Science

? Franceschini, F. and Maisano, D. (2011), Proposals for evaluating the regularity of a scientist’s research output. Scientometrics, 88 (1), 279-295.

Full Text: 2011\Scientometrics88, 279.pdf

Abstract: Evaluating the career of individual scientists according to their scientific output is a common bibliometric problem. Two aspects are classically taken into account: overall productivity and overall diffusion/impact, which can be measured by a plethora of indicators that consider publications and/or citations separately or synthesise these two quantities into a single number (e.g. h-index). A secondary aspect, which is sometimes mentioned in the rules of competitive examinations for research position/promotion, is time regularity of one researcher’s scientific output. Despite the fact that it is sometimes invoked, a clear definition of regularity is still lacking. We define it as the ability of generating an active and stable research output over time, in terms of both publications/quantity and citations/diffusion. The goal of this paper is introducing three analysis tools to perform qualitative/quantitative evaluations on the regularity of one scientist’s output in a simple and organic way. These tools are respectively (1) the PY/CY diagram, (2) the publication/citation Ferrers diagram and (3) a simplified procedure for comparing the research output of several scientists according to their publication and citation temporal distributions (Borda’s ranking). Description of these tools is supported by several examples.

Keywords: Bibliometric, Borda’s Method, Citation, Citation Regularity, Citation, Publication Distribution, Citations, Ferrers Diagram, h Index, h-Index, h-Index, Individual Scientist, Journals, Publication, Publication Regularity, Publications, Ranking, Research, Research Evaluation, Research Output

? Glänzel, W. and Thijs, B. (2011), Using ‘core documents’ for the representation of clusters and topics. Scientometrics, 88 (1), 297-309.

Full Text: 2011\Scientometrics88, 297.pdf

Abstract: The notion of ‘core documents’, first introduced in the context of co-citation analysis and later re-introduced for bibliographic coupling, refers to the representation of the core of a publication set according to given criteria. In the present study, the notion of core documents is extended to the combination of citation-based and textual links. It is shown that core documents defined this way can be used to represent and describe document clusters and topics at different levels of aggregation. Methodology is illustrated using the example of two ISI Subject Categories selected from applied and social sciences.

Keywords: Bibliographic, Bibliographic Coupling, Cluster Analysis, Combined Cocitation, Core Documents, Hybrid Clustering, Methodology, Publication, Science, Social Sciences, Text Mining, Word Analysis

? Leite, P., Mugnaini, R. and Leta, J. (2011), A new indicator for international visibility: exploring Brazilian scientific community. Scientometrics, 88 (1), 311-319.

Full Text: 2011\Scientometrics88, 311.pdf

Abstract: Brazilian science has increased fast during the last decades. An example is the increasing in the country’s share in the world’s scientific publication within the main international databases. But what is the actual weight of international publications to the whole Brazilian productivity? In order to respond this question, we have elaborated a new indicator, the International Publication Ratio (IPR). The data source was Lattes Database, a database organized by one of the main Brazilian S&T funding agency, which encompasses publication data from 1997 to 2004 of about 51,000 Brazilian researchers. Influences of distinct parameters, such as sectors, fields, career age and gender, are analyzed. We hope the data presented may help S&T managers and other S&T interests to better understand the complexity under the concept scientific productivity, especially in peripheral countries in science, such as Brazil.

Keywords: Age, Brazil, Brazilian Science, Databases, Impact, Index, International Publication Ratio, Productivity, Profile, Publication, Publications, Researchers, Science, Scientific Publication, Scientific Publications, Technology, Visibility, Women

? Ravallion, M. and Wagstaff, A. (2011), On measuring scholarly influence by citations. Scientometrics, 88 (1), 321-337.

Full Text: 2011\Scientometrics88, 321.pdf

Abstract: Bibliometric measures based on citations are widely used in assessing the scientific publication records of authors, institutions and journals. Yet currently favored measures lack a clear theoretical foundation and are known to have counter-intuitive properties. The paper proposes a new approach that is grounded on a theoretical “influence function,” representing explicit prior beliefs about how citations reflect influence. Conditions are derived for robust qualitative comparisons of influence-conditions that can be implemented using readily-available data. Two examples are provided, one using the world’s top-10 economics department, the other using the top-10 economics journals.

Keywords: Authors, Bibliometric, Citations, Economics, Economics Departments, Economics Journals, G-Index, h-Index, Inequality, Journals, Publication, Ranking, Scientific Influence, Scientific Publication

? Bensman, S.J. (2011), The publish or perish book: Your guide to effective and responsible citation analysis. Scientometrics, 88 (1), 339-342

Full Text: 2011\Scientometrics88, 339.pdf

Keywords: Citation, Citation Analysis, Google Scholar, Impact, Journals, Scopus

? Gao, X., Guan, J.C. and Rousseau, R. (2011), Mapping collaborative knowledge production in China using patent co-inventorships. Scientometrics, 88 (2), 343-362.

Full Text: 2011\Scientometrics88, 343.pdf

Abstract: Only a few cases of systematic empirical research have been reported investigating collaborative knowledge production in China and its implications for China’s national and regional innovation system. Using Chinese patent data in the US Patent and Trademark Office (USPTO), this paper examines the geographic variations in intraregional, inter-regional and international knowledge exchanges of China from 1985 to 2007. Degree centrality reveals that intraregional and international collaborations are the main channels of knowledge exchange for the provinces and municipalities of China while inter-regional knowledge exchange is relatively weak. Besides, over the two decades, the knowledge exchange network has been expanding (connecting an increasing number of provinces and countries), becoming more decentralized (increasing number of hubs) and more cohesive (more linkages). A blockmodel analysis further reveals that the inter-regional network of China begins to show characteristics of a core-periphery structure. The most active knowledge exchange occurs between members of the core block composed by the most advanced provinces while the members of the peripheral block from less favored regions have few or no local and extra-local knowledge exchange. Building a strong knowledge transfer network would much improve the innovation capacities in less favored regions and help them break out from their “locked-in” development trajectories.

Keywords: Authorship, China, Development, Diffusion, Exploration, Geographical Proximity, Innovation, Innovation System, Knowledge Exchange, Knowledge Transfer, Networks, Patent, Regions, Research, Scientific Collaboration, Spillovers, Universities, US

? Egghe, L. (2011), The influence of random removal of sources and items on the h-index. Scientometrics, 88 (2), 363-370.

Full Text: 2011\Scientometrics88, 363.pdf

Abstract: If we have two information production processes with the same h-index, random removal of items causes one system to have a higher h-index than the other system while random removal of sources causes the opposite effect. In a Lotkaian framework we prove formulae for the h-index in case of random removal of items and in case of random removal of sources. In conclusion, we warn for the use of the h-index in case of incomplete data sets.

Keywords: h Index, h-Index, Hirsch-Index, Hirsch-Index, Information, Items, Random Removal, Sources, Transformations

? Andersen, J.P. and Hammarfelt, B. (2011), Price revisited: On the growth of dissertations in eight research fields. Scientometrics, 88 (2), 371-383.

Full Text: 2011\Scientometrics88, 371.pdf

Abstract: This paper studies the production of dissertations in eight research fields in the natural sciences, the social sciences and the humanities. In using doctoral dissertations it builds on De Solla Prices seminal study which used PhD dissertations as one of several indicators of scientific growth (Price, Little science, big science, 1963). Data from the ProQuest: Dissertations and Theses database covering the years 1950-2007 are used to depict historical trends, and the Gompertz function was used for analysing the data. A decline in the growth of dissertations can be seen in all fields in the mid-eighties and several fields show only a modest growth during the entire period. The growth profiles of specific disciplines could not be explained by traditional dichotomies such as pure/applied or soft/hard, but rather it seems that the age of the discipline appears to be an important factor. Thus, it is obvious that the growth of dissertations must be explained using several factors emerging both inside and outside academia. Consequently, we propose that the output of dissertations can be used as an indicator of growth, especially in fields like the humanities, where journal or article counts are less applicable.

Keywords: Dissertations, Growth of Science, History of Science, Journal, Models, Publication Analysis, Research, Social Sciences

? Albarran, P., Crespo, J.A., Ortuno, I. and Ruiz-Castillo, J. (2011), The skewness of science in 219 sub-fields and a number of aggregates. Scientometrics, 88 (2), 385-397.

Full Text: 2011\Scientometrics88, 385.pdf

Abstract: This paper studies evidence from Thomson Scientific (TS) about the citation process of 3.7 million articles published in the period 1998-2002 in 219 Web of Science (WoS) categories, or sub-fields. Reference and citation distributions have very different characteristics across sub-fields. However, when analyzed with the Characteristic Scores and Scales (CSS) technique, which is replication and scale invariant, the shape of these distributions over three broad categories of articles appears strikingly similar. Reference distributions are mildly skewed, but citation distributions with a 5-year citation window are highly skewed: the mean is 20 points above the median, while 9-10% of all articles in the upper tail account for about 44% of all citations. The aggregation of sub-fields into disciplines and fields according to several aggregation schemes preserve this feature of citation distributions. It should be noted that when we look into subsets of articles within the lower and upper tails of citation distributions the universality partially breaks down. On the other hand, for 140 of the 219 sub-fields the existence of a power law cannot be rejected. However, contrary to what is generally believed, at the sub-field level the scaling parameter is above 3.5 most of the time, and power laws are relatively small: on average, they represent 2% of all articles and account for 13.5% of all citations. The results of the aggregation into disciplines and fields reveal that power law algebra is a subtle phenomenon.

Keywords: Characteristic Scores, Citation, Citation Analysis, Citations, Distributions, Indicators, Networks, Power Laws, Research Performance, Scales, Scientific Performance, Scores, Statistics, Web of Science

? Lv, P.H., Wang, G.F., Wan, Y., Liu, J., Liu, Q. and Ma, F.C. (2011), Bibliometric trend analysis on global graphene research. Scientometrics, 88 (2), 399-419.

Full Text: 2011\Scientometrics88, 399.pdf

Abstract: Graphene is a rising star as one of the promising materials with many applications. Its global literature increased fast in recent years. In this work, bibliometric analysis and knowledge visualization technology were applied to evaluate global scientific production and developing trend of graphene research. The data were collected from 1991 to 2010 from the Science Citation Index database, Conference Proceeding Citation Index database and Derwent Innovation Index database integrated by Thomson Reuters. The published papers from different subjects, journals, authors, countries and keywords distributed in several aspects of research topics proved that graphene research increased rapidly over past 20 years and boosted in recent 5 years. The distinctions in knowledge map show that the clusters distributed regularly in keywords of applied patents in recent 5 years due to the potential applications of graphene research gradually found. The analytical results provided several key findings of bibliometrics trend.

Keywords: Authors, Bibliometric, Bibliometric Analysis, Bibliometrics, Carbon-Films, Citation, Co-Authorship, Co-Words, Conference, Epitaxial Graphene, Graphene, Innovation, Journals, Knowledge Mapping, Literature, Papers, Research, Research Trend, Science, Science Citation Index, Trend

? Campanario, J.M. and Coslado, M.A. (2011), Benford’s law and citations, articles and impact factors of scientific journals. Scientometrics, 88 (2), 421-432.

Full Text: 2011\Scientometrics88, 421.pdf

Abstract: First order digits in data sets of natural and social data often follow a distribution called Benford’s law. We studied the number of articles published, citations received and impact factors of all journals indexed in the Science Citation Index from 1998 to 2007. We tested their compliance with Benford’s law. Citations data followed Benford’s law remarkably well in all years studied. However, for the data on the numbers of articles, the differences between the values predicted by Benford’s law and the observed values were always statistically significant. This was also the case for most data for impact factors.

Keywords: Articles, Benford Law, Citation, Citations, Compliance, Impact, Impact Factor, Journals, Science Citation Index

? Chen, Y.S. (2011), Using patent analysis to explore corporate growth. Scientometrics, 88 (2), 433-448.

Full Text: 2011\Scientometrics88, 433.pdf

Abstract: This study applies patent analysis to discuss the influences of the three aspects of patent trait-a firm’s revealed technology advantage in its most important technological field (RTA(MIT)), relative patent position in its most important technological field (RPPMIT), and patent share in its most important technological field (PSMIT)-upon corporate growth and discusses the moderation effect of relative growth rate of its most important technological field (RGR(MIT)) in the American pharmaceutical industry. The results demonstrate that the three relationships between corporate growth and the three aspects of patent trait are positive, and verify that RGR(MIT) moderates the three relationships. This study suggests that pharmaceutical companies should enhance their R&D capabilities, the degree of leading position, and concentration of R&D investment in their most important technological fields to increase their growth. Finally, this study classifies the pharmaceutical companies into four types, and provides some suggestions to them.

Keywords: Citations, Companies, Competences, Corporate Growth, Development Performance, Firm, Market Value, Patent, Patent Analysis, Patent Share (PS), Pharmaceutical Companies, Pharmaceutical-Industry, Portfolios, Productivity, Relative Patent Position (RPP), Research-And-Development, Revealed Technology Advantage (RTA)

? Barnett, G.A., Huh, C., Kim, Y. and Park, H.W. (2011), Citations among communication journals and other disciplines: A network analysis. Scientometrics, 88 (2), 449-469.

Full Text: 2011\Scientometrics88, 449.pdf

Abstract: This article describes the results of a network analysis based on the citation among Communication journals and those academic disciplines that are cited by those journals labeled as “Communication” by the Web of Science. The results indicate that the journals indexed solely as Communication rather than those also tagged as another social science are more central in the citation network. Further, a cluster analysis of the cited disciplines revealed three groupings, a micro psychological cluster, a macro socio-political group and a woman’s studies clique. A two-mode network analysis found that the most central Communication journals cited multiple clusters, while the peripheral journals cited only one, suggesting that the structure of influence on the field of Communication is more complex than suggested by Park and Leydesdorff (Scientometrics 81(1):157-175, 2009). Also, the results indicate that the macro cluster is about twice as influential as the micro cluster, rather than as Park and Leydesdorff suggest that Psychology is the discipline’s primary influence.

Keywords: Association, Centrality, Citation, Citation Analysis, Citations, Communication, Field, Journals, Network Analysis, Patterns, Primary, Psychology, Science, Scientometrics, Web of Science

? Toivanen, H. and Ponomariov, B. (2011), African regional innovation systems: Bibliometric analysis of research collaboration patterns 2005-2009. Scientometrics,