A scientometrics law about co-authors and their ranking: the co-author core

Rather than “measuring” a scientist impact through the number of citations which his/her published work can have generated, isn’t it more appropriate to consider his/her value through his/her scientific network performance illustrated by his/her co-author role, thus focussing on his/her joint publications, and their impact through citations? Whence, on one hand, this paper very briefly examines bibliometric laws, like the h-index and subsequent debate about co-authorship effects, but on the other hand, proposes a measure of collaborative work through a new index. Based on data about the publication output of a specific research group, a new bibliometric law is found. Let a co-author C have written J (joint) publications with one or several colleagues. Rank all the co-authors of that individual according to their number of joint publications, giving a rank r to each co-author, starting with r = 1 for the most prolific. It is empirically found that a very simple relationship holds between the number of joint publications J by coauthors and their rank of importance, i.e., J ∝ 1/r. Thereafter, in the same spirit as for the Hirsch core, one can define a “co-author core”, and introduce indices operating on an author. It is emphasized that the new index has a quite different (philosophical) perspective that the h-index. In the present case, one focusses on “relevant” persons rather than on “relevant” publications. Although the numerical discussion is based on one “main author” case, and two “control” cases, there is little doubt that the law can be verified in many other situations. Therefore, variants and generalizations could be later produced in order to quantify co-author roles, in a temporary or long lasting stable team(s), and lead to criteria about funding, career measurements or even induce career strategies.     

Validating indicators of interdisciplinarity: linking bibliometric measures to studies of engineering research labs

This article examines the extent to which specific features of interdisciplinary research are accurately reflected in selected bibliometric measures of scholarly publications over time. To test the validity of these measures, we compare knowledge of research processes and impact based on ethnographic studies of a well-established researcher’s laboratory, together with personal interview data, against bibliometric indicators of cognitive integration, diffusion, and impact represented in the entire portfolio of papers produced by this researcher over time.     

Community evolution analysis based on co-author network: a case study of academic communities of the journal of “Annals of the Association of American Geographers”

Academic community evolution reveals the development of scientific collaboration among scientists. These social interactions of researchers can be well reflected by co-author network, making it feasible to investigate academic community through looking into co-author network, and to study community evolution through dynamic co-author network analysis. Existing metrics measure an author’s impact or centrality in co-author network individually, rather than considering the academic community as a whole. Besides, co-authors of a paper usually make different contributions reflected in the name order, which is often ignored in traditional co-author network analysis. Furthermore, attention has been paid mainly on those structure-level characteristics like the small-world coefficient and the clustering coefficient, the content-level characteristics like community, author, and topics, however, are crucial in the understanding of community evolution. To address those problems, we firstly propose a “comprehensive impact index” to evaluate the author in a co-author network by comprehensively considering the statistic-based impact and the network-based centrality. Then the comprehensive index value of all authors in a community is added up to evaluate the community as a whole. Further, a lifecycle strategy is proposed for the community evolution analysis. Taking geography academic community as a pilot study, we select 919 co-authored papers from the flagship journal of “Annals of the Association of American Geographers”. The co-author groups are generated by community detection method. Top three co-author groups are identified through computing with the proposed index and analyzed through the proposed lifecycle strategy from perspective of community structures, member authors, and impacts respectively. The results demonstrate our proposed index and strategy are more efficient for analyzing academic community evolution than traditional methods.     

A new approach to analyzing patterns of collaboration in co-authorship networks: mesoscopic analysis and interpretation

This paper focuses on methods to study patterns of collaboration in co-authorship networks at the mesoscopic level. We combine qualitative methods (participant interviews) with quantitative methods (network analysis) and demonstrate the application and value of our approach in a case study comparing three research fields in chemistry. A mesoscopic level of analysis means that in addition to the basic analytic unit of the individual researcher as node in a co-author network, we base our analysis on the observed modular structure of co-author networks. We interpret the clustering of authors into groups as bibliometric footprints of the basic collective units of knowledge production in a research specialty. We find two types of coauthor-linking patterns between author clusters that we interpret as representing two different forms of cooperative behavior, transfer-type connections due to career migrations or one-off services rendered, and stronger, dedicated inter-group collaboration. Hence the generic coauthor network of a research specialty can be understood as the overlay of two distinct types of cooperative networks between groups of authors publishing in a research specialty. We show how our analytic approach exposes field specific differences in the social organization of research.     

Bibliometric characteristics of highly cited papers from Taiwan, 2000–2009

The present study analyzes bibliometric characteristics of Taiwan??s highly cited papers published from 2000 to 2009. During this period, Taiwan ranked within the top 30 countries by number of highly cited papers, defined in Thomson Reuters?? Essential Science Indicators (ESI) as those that rank in the top 1?% by citations for their category and year of publication. Taiwan made notable progress in world-class research in the two consecutive 5-year periods 2000?C2004 and 2005?C2009. For the group of highly cited papers from Taiwan, USA, China, Germany, and Japan were the top collaborating countries over the decade. In recent years, Taiwan has increasingly collaborated with European countries whose output of highly cited papers is relatively high and increasing, rather than with its neighboring countries in Asia. Overall, Taiwan produced highly cited papers in all the 22 ESI subject categories during the 10-year period. Taiwan??s output of highly cited papers was greatest in the categories of Engineering, Clinical Medicine, and Physics, while those in Agricultural Sciences and Mathematics exceeded the expected output level in relative terms. More detailed analyses would be useful for a holistic understanding of Taiwan??s research landscape and their progress in world-class research, combining both bibliometric and non-bibliometric data, such as researcher mobility, research grants, and output from internationally-collaborated research programs.     

A boosted-trees method for name disambiguation

This paper proposes a method for classifying true papers of a set of focal scientists and false papers of homonymous authors in bibliometric research processes. It directly addresses the issue of identifying papers that are not associated (??false??) with a given author. The proposed method has four steps: name and affiliation filtering, similarity score construction, author screening, and boosted trees classification. In this methodological paper we calculate error rates for our technique. Therefore, we needed to ascertain the correct attribution of each paper. To do this we constructed a small dataset of 4,253 papers allegedly belonging to a random sample of 100 authors. We apply the boosted trees algorithm to classify papers of authors with total false rate no higher than 30% (i.e. 3,862 papers of 91 authors). A one-run experiment achieves a testing misclassification error 0.55%, testing recall 99.84%, and testing precision 99.60%. A 50-run experiment shows that the median of testing classification error is 0.78% and mean 0.75%. Among the 90 authors in the testing set (one author only appeared in the training set), the algorithm successfully reduces the false rate to zero for 86 authors and misclassifies just one or two papers for each of the remaining four authors.     

Research quality and diversity of funding: A model for relating research money to output of research

We analyze the relation between funding and output using bibliometric methods with field normalized data. Our approach is to connect individual researcher data on funding from Swedish university databases to data on incoming grants using the specific personal ID-number. Data on funding include the person responsible for the grant. All types of research income are considered in the analysis yielding a project database with a high level of precision. Results show that productivity can be explained by background variables, but that quality of research is more or less un-related to background variables.     

An item-by-item subject classification of papers published in multidisciplinary and general journals using reference analysis

A serious shortcoming of bibliometric studies based on the(Social) Science (s) Citation Index is the lack of an universally applicable subject classification scheme as individual papers are concerned. Subject classification of papers on the basis of assigning journals to subject categories (like those found in the various supplements of ISI databases) works well in case of highly specialised journals, but fails for multidisciplinary journals such asNature, Science andPNAS—and so far as subfields are taken into consideration-also for “general” journals (e.g.JACS orAngewandte Chemie). This study presents the results of a pilot project attempting to overcome this shortcoming by delimiting the subject of papers published in multidisciplinary and general journals by an item-by-item subject classification scheme, where assignment is based on the analysis of the subject classification of reference literature. The results clearly confirmed the conclusions of earlier studies by the authors in the field of reference analysis. For the really important journals (sufficiently high number of annual publications and high impact with respect to the field), the share of classifiable papers was surprisingly high, and the assignment proved reliable as well. Since papers in the leading general and multidisciplinary journals are frequently citing general and multidisciplinary journals, an iterated application of the procedure is expected to increase the number of classifiable publications. The results of the new methodology may improve the validity of bibliometric studies for research evaluation purposes.     

Competition for funding as an indicator of research competitiveness

Summary Research quality is the cornerstone of modern science, it is used in the understanding of reputational differences among scientific and academic institutions. Traditionally, scientific activity is measured by a set of indicators and well-established bibliometric techniques based on the number of academic papers published in top-ranked journals or on the number of citations of these papers. These indicators are usually critical in measuring differences in research performance, both at individual and at scientific institutional levels. In this paper, we introduce an alternative and complementary set of indicators based on the results of competition for research funding, that aims to enlarge the framework in which research performance has traditionally been measured. Theoretical support for this paper is found in the role that the search for funding plays in the researchers’ credibility cycle as well as in peer review, the basic instrument for the allocation of public R&D funds. Our method analyses the outcomes of the researchers’ struggle for funding, using data from research proposal applications and awards, as the unit of observation, and aggregating them by research institutions to rank them in relative scales of research competitiveness.     

Collaboration network and pattern analysis: case study of dye-sensitized solar cells

Nowadays, the development of emerging technology has become a double-edged sword in the scientific world. It can not only bring lots of innovation to society, but may also cause some terrible consequences due to its unknown factors. International collaboration may be able to reduce risks, which means a lot to the exploration of the emerging technology. Taking dye-sensitized solar cells (DSSCs) as an example, this paper examines the rapid growth of Chinese DSSCs research and the rise of collaboration between China and other countries/region. We use bibliometric and social network analysis methods to explore the patterns of scientific collaboration at country, institution and individual levels using data from the Science Citation Index. Examining overall trends shows that China has increased her position in DSSCs around the world. Furthermore, by focusing on the individual level, we find that the most influential authors tend to have fixed co-author networks and author name order, which is something worth considering. We use co-author analysis software independently developed to check three kinds of fixed co-author networks to explore author contributions, influence, and Author Activity Index rank in collaboration networks and use the rank we calculated to further explain author contributions in the networks. Results show that Chinese-X (e.g., Chinese-American) authors have pushed the collaboration between country and country and almost every kind of small network has a top author in it to gather others together. The modified author activity index rank list may reflect real research level. Author collaboration patterns have been impacted by the kinds of their institutions to some degree. These results can undoubtedly promote the international collaboration and the innovation process in the similar emerging technology fields.     

A comparison of astronomy in fifteen member countries of the organisation for economic co-operation and development

Various data are collected for 15 member countries of the Organisation for Economic Cooperation and Development (OECD) that have to do with the practising of astronomy: (1) using the report of the Astronomy expert meeting of the Megascience Forum of the OECD, the level of astronomy funding, size of the research communities, relative commitment to ground-based versus space-based astronomy, etc.; (2) from other sources the size of the population, Gross National Product and size of the total research community; (3) from the paper ofSchubert et al. (1989) data on publication and citation scores of these countries in astronomy and the total research effort (excluding social and economic sciences). Using these data the 15 countries have been ranked on: (1) the relative level of astronomy funding; (2) the relative level of performance in astronomy; (3) the correspondence between funding and performance in astronomy; (4) the relative level of performance of the total science effort; and (5) the performance in astronomy relative to that in all sciences.The results of this study have been summarized in table 10 below. Other interesting results that can be inferred from the data collected in this paper are: (1) one out of every 75,000 inhabitants of these OECD countries is an astronomical researcher; (2) each citizen of these countries spends on average 2.5 $ per year on astronomical research (either from the ground or in space); (3) the average budget per researcher amounts to roughly 200,000 $ per annum; (4) the average budget for astronomy amounts to 0.016% of the Gross National Product and of order 1% of the total budget for civilian R & D; (5) an astronomical researcher from these countries produces on average 1.7 papers each year and these papers receive on average ten citations in the first five years; (6) researchers in science (excluding economic and social sciences) make up 0.08% of the population in these countries and one in about 65 of these researchers works in astronomy or astrophysics; (7) most countries spend about one-third of their astronomy budget on salaries, one-sixth on basic support and half on observing facilities (in a ratio one to two for ground-based versus space).     

Characteristics of research in China assessed with Essential Science Indicators

To provide an overview of the characteristics of research in China, a bibliometric evaluation of highly cited papers with high-level representation was conducted during the period from 1999 to 2009 based on the Essential Science Indicators (ESI) database. A comprehensive assessment covered overall performance, journals, subject categories, internationally collaborative countries, national inter-institutionally collaborative institutions, and most-cited papers in 22 scientific fields. China saw a strong growth in scientific publications in the last decade, to some extent due to increasing research and development expenditure. China has been more active in ESI fields of chemistry and physics, but more excellent in materials science, engineering and mathematics. Most publications were concerned with the common Science Citation Index subject categories of multidisciplinary chemistry, multidisciplinary materials and science, and physical chemistry. About one half China’s ESC papers were internationally collaborative and the eight major industrialized countries (the USA, Germany, the UK, Japan, France, Canada, Russia, and Italy) played a prominent role in scientific collaboration with China, especially the USA. The Chinese Academy of Sciences took the leading position of institutions with many branches. The “985 Project” stimulated the most productive institutions for academic research with a huge funding injection and the universities in Hong Kong showed good scientific performance. The citation impact of internationally collaborative papers differed among fields and international collaborations made positive contributions to academic research in China.     

Does the Scopus author ID suffice to track scientific international mobility? A case study based on Leibniz laureates

In this paper I outline how author identifiers enable to track international mobility of scientists. Authorship systems help to distinguish among similar names and provide information on affiliations and thus countries of stay. This study explores the relation between CV data and Scopus data in regard to tracking international mobility of scientists. To test the consistency and applicability of data on mobility episodes, residence countries as provided in CVs of a set of German scientists were compared against country information in the affiliations of their publications. Therefore, the CVs of Leibniz laureates were coded for the period 1996–2015 and their publications were gathered on the basis of Scopus author ID. Results show that the majority of scientists under study have a single author ID (68.4%). However, there are laureates with so-called ‘split identities’ where more than one author ID exists. Most of them have a dominant author ID that covers the majority of their publications and one or more additional IDs with only a few publications causing these split identities. Recall statistic shows that the use of the dominant author ID of each laureate would result in around 97% of their publication output. In contrast, the precision of Scopus author ID proves to be high. A random sample shows that all publications assigned to a specific author ID relate to a single individual, so that the precision statistic would yield 100%. Further results show that the registry systems ORCID and ResearcherID are no alternatives to Scopus author ID, because a minority of laureates make use of these identifier systems and data is often incomplete. Unlike ORCID and ResearcherID that suffer from a selection bias as those scientists who remain in science maintain their author profiles, Scopus author ID exists for every author publishing in sources covered by Scopus. The comparison of mobility data in Scopus versus CV data shows that bibliometric data is suitable to identify a scientist’s international mobility and appears to be a good solution if there are no CVs available or if they are incomplete. Furthermore, the reasons for inconsistencies in mobility data are discussed. These mainly reside in the lack of co-author affiliations, incomplete CV data, and other minor reasons.     

Quantitative analysis of collaborative and mobility networks

This study proposes a quantitative analysis of researcher mobility (i.e. transfer from one institution to another) and collaborative networks on the basis of author background data extracted from biographical notes in scientific articles to identify connections that are not revealed via simple co-authorship analysis. Using a top-ranked journal in the field of computer vision, we create a layered network that describes various aspects of author backgrounds, demonstrating a geographical distribution of institutions. We classify networks according to various dimensions including authors, institutions and countries. The results of the quantitative analysis indicate that mobility networks extend beyond the typical collaborative networks describing institutional and international relationships. We also discuss sectoral collaboration considering the mobility networks. Our findings indicate a limitation of collaborative analysis based on bibliometric data and the importance of tracing researcher mobility within potential networks to identify the true nature of scientific collaboration.     

The fruits of collaboration in a multidisciplinary field

Collaboration between researchers and between research organizations is generally considered a desirable course of action, in particular by some funding bodies. However, collaboration within a multidisciplinary community, such as the Computer–Human Interaction (CHI) community, can be challenging. We performed a bibliometric analysis of the CHI conference proceedings to determine if papers that have authors from different organization or countries receive more citations than papers that are authored by members of the same organization. There was no significant difference between these three groups, indicating that there is no advantage for collaboration in terms of citation frequency. Furthermore, we tested if papers written by authors from different organizations or countries receive more best paper awards or at least award nominations. Papers from only one organization received significantly fewer nominations than collaborative papers.     

An attempt of surveying and classifying bibliometric indicators for scientometric purposes

An attempt is made for the survey and classification of bibliometric indicators applicable for assessment of publication performance of researchers active in natural sciences. Indicators can be classified as publication and citation ones which may refer to impact and quantity of publication activity of researcher(s), teams, institutes or countries. Taking into account the possible reference standards, the indicators are classified as simple, specific, balance, distribution and relative ones. In order to evaluate publication activity both qualitatively and quantitatively, relative citation indicators can be recommended, which relate citations received to the sum of impact factors of the journals, where the papers were published or give the relative measure of the average citedness of papers related to that of papers in journals in a similar subfield.     

Knowledge linked to museum specimen vouchers: measuring scientific production from a major biological collection in Colombia

Biological collections are sources of knowledge, particularly critical to understand life when they house specimens from megadiverse countries. However, the scientific value of biological collections is usually unknown because the lack of an explicit link between knowledge and specimens. Here we compiled 628 papers from 152 journals that used collection objects from the Colecciones Biológicas del Instituto de Investigación de Recursos Biológicos Alexander von Humboldt, Colombia (IAvH-CB) as sources. The compilation was largely based on expert knowledge. However, to assess the performance of our method we compared our results with results obtained conducting automatic searches in academic databases. We calculated different metrics and depicted geographical, taxonomic, and bibliometric trends. We found that geographic coverage of the IAvH-CB objects used in the studies is largely regional or national. Taxonomically, we found records of 176 families in 61 orders of taxa, but there is large variation among the number of studies in different groups. The bibliometric analyses indicated that there is a growing trend in the number of publications and citations over the years, and that the citation number as well as the H index of this set of papers is comparable to the knowledge produced by major researchers in Colombia and of similar magnitude to that of the production of relatively small or medium sized collections in the USA. The compilation method used performed well, with broad coverage and an omission rate below 8%, compared with automated searches. However, we conclude that both approaches, expert knowledge and automated searches, are complementary. IAvH-CB are a massive source of scientific knowledge about Colombian biodiversity and they are instrumental for documenting basic issues about taxa in the country.     

Exploiting similarities across multiple dimensions for author name disambiguation

Scientometrics - In bibliometric analysis, ambiguity in author names may lead to erroneous aggregation of records. The author name disambiguation techniques attempt to address this issue by...     

A bibliometric analysis of NOAA’s Office of Ocean Exploration and Research

Bibliometric analysis techniques are increasingly being used to analyze and evaluate scientific research produced by institutions and grant funding agencies. This article uses bibliometric methods to analyze journal articles funded by NOAA’s Office of Ocean Exploration and Research (OER), an extramural grant-funding agency focused on the scientific exploration of the world’s oceans. OER-supported articles in this analysis were identified through grant reports, personal communication, and acknowledgement of OER support or grant numbers. The articles identified were analyzed to determine the number of publications and citations received per year, subject, and institution. The productivity and citation impact of institutions in the US receiving OER grant funding were mapped geographically. Word co-occurrence and bibliographic coupling networks were created and visualized to identify the research topics of OER-supported articles. Finally, article citation counts were evaluated by means of percentile ranks. This article demonstrates that bibliometric analysis can be useful for summarizing and evaluating the research performance of a grant funding agency.