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Measuring the novelty of scientific papers is an important research topic. If most subsequent researches of a focal paper only cite itself instead of citing its references as well, this paper could be highly disruptive as it may start a new stream of research. However, due to preferential attachment, even if a focal paper is very disruptive, the subsequent works may still cite both the focal paper and some of its highly cited references. To eliminate the noise caused by these highly cited references, we modify the disruption metric and analyze its performance and robustness. The results show that the improved method could better distinguish Nobel prize winning papers from the others. In addition, the resultant ranking is more stable against the highly cited references and random link removal on citation network. [ABSTRACT FROM AUTHOR]

In research evaluation of single researchers, the assessment of paper and journal impact is of interest. High journal impact reflects the ability of researchers to convince strict reviewers, and high paper impact reflects the usefulness of papers for future research. In many bibliometric studies, metrics for journal and paper impact are separately presented. In this paper, we introduce two graph types, which combine both metrics in a single graph. The graphs can be used in research evaluation to visualize the performance of single researchers comprehensively. [ABSTRACT FROM AUTHOR]

The unusual citation profile of the 1985 Physics Nobel Prize paper has been analyzed. The number of citing papers per year exhibits a maximum of 123 citations in the mid-1980s and increases to more than 200 citations about two decades later. The publication set of the citing papers was analyzed in terms of co-authorships and research topics. The USA and (more recently) the People's Republic of China appear prominently among the countries of the citing authors. A keyword analysis of the citing papers revealed research dealing with topological insulators as one of the major newly evolving research topics. An analysis of the co-cited papers has been performed via reference publication year spectroscopy (RPYS). The most-frequently co-cited papers (the peak papers of the RPYS spectrogram) were identified and discussed. As a result, we found two primary booster papers and three secondary booster papers that renewed the interest in the 1985 Physics Nobel Prize paper. [ABSTRACT FROM AUTHOR]

Bibliometric information retrieval in databases can employ different strategies. Commonly, queries are performed by searching in title, abstract and/or author keywords (author vocabulary). More advanced queries employ database keywords to search in a controlled vocabulary. Queries based on search terms can be augmented with their citing papers if a research field cannot be curtailed by the search query alone. Here, we present another strategy to discover the most important papers of a research field. A marker paper is used to reveal the most important works for the relevant community. All papers co-cited with the marker paper are analyzed using reference publication year spectroscopy (RPYS). For demonstration of the marker paper approach, density functional theory is used as a research field. Comparisons between a prior RPYS on a publication set compiled using a keyword-based search in a controlled vocabulary and three different co-citation RPYS analyses show very similar results. Similarities and differences are discussed. [ABSTRACT FROM AUTHOR]

According to the data from the Scopus publication database, as analyzed in several recent studies, more than 70,000 papers have been published in the area of Software Engineering (SE) since late 1960's. According to our recent work, 43% of those papers have received no citations at all. Since citations are the most commonly used metric for measuring research (academic) impact, these figures raise questions (doubts) about the (non-existing) impact of such a large set of papers. It is a reality that typical academic reward systems encourage researchers to publish more papers and do not place a major emphasis on research impact. To shed light on the issue of volume (quantity) versus citation-based impact of SE research papers, we conduct and report in this paper a quantitative bibliometrics assessment in four aspects: (1) quantity versus impact of different paper types (e.g., conference versus journal papers), (2) ratios of uncited (non-impactful) papers, (3) quantity versus impact of papers originating from different countries, and (4) quantity versus impact of papers by each of the top-10 authors (in terms of number of papers). To achieve the above objective, we conducted a quantitative exploratory bibliometrics assessment, comprised of four research questions, to assess quantity versus impact of SE papers with respect to the aspects discussed above. We extracted the data through a systematic, automated and repeatable process from the Scopus paper database, which we also used in two previous papers. Our results show that the distribution of SE publications has a major inequality in terms of impact overall, and also when categorized in terms of the above four aspects. The situation in the SE literature is similar to the other areas of science as studied by previous bibliometrics studies. Also, among our results is the fact that journal articles and conference papers have been cited 12.6 and 3.6 times on average, confirming the expectation that journal articles have more impact, in general, than conference papers. Also, papers originated from English-speaking countries have in general more visibility and impact (and consequently citations) when compared to papers originated from non-English-speaking countries. Our results have implications for improvement of academic reward systems, which nowadays mainly encourage researchers to publish more papers and usually neglect research impact. Also, our results can help researchers in non-English-speaking countries to consider improvements to increase their research impact of their upcoming papers. [ABSTRACT FROM AUTHOR]

In science, sleeping papers, previously known as “Sleeping Beauties”, refer to scientific papers that are recognized by the scientific community after a long hibernation period following their publication. Many factors may contribute to their delayed yet exceptional popularity, such as the introduction of new technologies or ideas that are beyond the capabilities at the time of publication. The recognition of a sleeping paper, often through a paper that cites the sleeping paper and has a profound impact on the research area, is important to the scientific community. Here, we proposed a method to identify the paper that rediscovers a sleeping paper, known as a rediscovering paper, based on the citation network of the sleeping paper. Based on the 15 rediscovering papers obtained from the top sleeping papers in science, we introduced 5 feature indices of the leading authors of these rediscovering papers (rediscovering authors) defined by an academic search system AMiner (https://cn.aminer.org/). The 5 feature indices depict academic achievements of researchers from various aspects: Publication, Citation, Longevity, H-index and Sociability. The rediscovering authors lead to most general scientific authors in the 5 feature indices. Our results reveal common features of potential rediscovering authors in the scientific community who may play significant roles in the propagation of citation networks. [ABSTRACT FROM AUTHOR]

Citation information helps researchers observe the evolution of the knowledge. In scientific publications, a review paper discusses a professional field and thus tends to have more citations than general papers do. This study investigated whether specific characteristics of review papers induce different results in citation-based analysis. From the Scopus database, we collected scientific publications in a specific research field, e-tourism, to examine the role of review papers in citation-based analysis. The dataset includes 1421 publications covering the period from the 1988-2015. Empirical statistics show that review papers' specific citation patterns influence citation analysis. First, in the main path analysis, the result expresses review papers' integrative role in linking papers from diverse perspectives toward a clear mainstream topic. Second, in a well-defined research context, review papers introduce bias in citation-based clustering analysis because the specific high citation pattern in review papers obfuscates the grouping process. When using citation information in analysis, scholars must consider the purpose of the study and treat review papers distinctly to avoid bias when using certain analysis methods and datasets. [ABSTRACT FROM AUTHOR]

Citation counts have long been considered as the primary bibliographic indicator for evaluating the quality of research—a practice premised on the assumption that citation count is reflective of the impact of a scientific publication. However, identifying several limitations in the use of citation counts alone, scholars have advanced the need for multifaceted quality evaluation methods. In this study, we apply a novelty indicator to quantify the degree of citation similarity between a focal paper and a pre-existing same-domain paper from various fields in the natural sciences by proposing a new way of identifying papers that fall into the same domain of focal papers using bibliometric data only. We also conduct a validation analysis, using Japanese survey data, to confirm its usefulness. Employing ordered logit and ordinary least squares regression models, this study tests the consistency between the novelty scores of 1871 Japanese papers published in the natural sciences between 2001 and 2006 and researchers' subjective judgments of their novelty. The results show statistically positive correlations between novelty scores and researchers' assessment of research types reflecting aspects of novelty in various natural science fields. As such, this study demonstrates that the proposed novelty indicator is a suitable means of identifying the novelty of various types of natural scientific research. [ABSTRACT FROM AUTHOR]

Keeping track of translational research is essential to evaluating the performance of programs on translational medicine. Despite several indicators in previous studies, a consensus measure is still needed to represent the translational features of biomedical research at the article level. In this study, we first trained semantic representations of biomedical entities and documents (i.e., bio-entity2vec and bio-doc2vec) based on over 30 million PubMed articles. With these vectors, we then developed a new measure called Translational Progression (TP) for tracking biomedical articles along the translational continuum. We validated the effectiveness of TP from two perspectives (Clinical trial phase identification and ACH classification), which showed excellent consistency between TP and other indicators. Meanwhile, TP has several advantages. First, it can track the degree of translation of biomedical research dynamically and in real-time. Second, it is straightforward to interpret and operationalize. Third, it doesn't require labor-intensive MeSH labeling and it is suitable for big scholarly data as well as papers that are not indexed in PubMed. In addition, we examined the translational progressions of biomedical research from three dimensions (including overall distribution, time, and research topic), which revealed three significant findings. The proposed measure in this study could be used by policymakers to monitor biomedical research with high translational potential in real-time and make better decisions. It can also be adopted and improved for other domains, such as physics or computer science, to assess the application value of scientific discoveries. [ABSTRACT FROM AUTHOR]

In this short communication, we provide an overview of a relatively newly provided source of altmetrics data which could possibly be used for societal impact measurements in scientometrics. Recently, Altmetric-a start-up providing publication level metrics-started to make data for publications available which have been mentioned in policy-related documents. Using data from Altmetric, we study how many papers indexed in the Web of Science (WoS) are mentioned in policy-related documents. We find that less than 0.5% of the papers published in different subject categories are mentioned at least once in policy-related documents. Based on our results, we recommend that the analysis of (WoS) publications with at least one policy-related mention is repeated regularly (annually) in order to check the usefulness of the data. Mentions in policy-related documents should not be used for impact measurement until new policy-related sites are tracked. [ABSTRACT FROM AUTHOR]

During Eugene Garfield’s (EG’s) lengthy career as information scientist, he published about 1500 papers. In this study, we use the impressive oeuvre of EG to introduce a new type of bibliometric networks: keyword co-occurrences networks based on the context of citations, which are referenced in a certain paper set (here: the papers published by EG). The citation context is defined by the words which are located around a specific citation. We retrieved the citation context from Microsoft Academic. To interpret and compare the results of the new network type, we generated two further networks: co-occurrence networks which are based on title and abstract keywords from (1) EG’s papers and (2) the papers citing EG’s publications. The comparison of the three networks suggests that papers of EG and citation contexts of papers citing EG are semantically more closely related to each other than to titles and abstracts of papers citing EG. This result accords with the use of citations in research evaluation that is based on the premise that citations reflect the cognitive influence of the cited on the citing publication. [ABSTRACT FROM AUTHOR]

In over five years, Bornmann, Stefaner, de Moya Anegon, and Mutz (2014b) and Bornmann, Stefaner, de Moya Anegón, and Mutz (2014c, 2015) have published several releases of the www.excellencemapping.net tool revealing (clusters of) excellent institutions worldwide based on citation data. With the new release, a completely revised tool has been published. It is not only based on citation data (bibliometrics), but also Mendeley data (altmetrics). Thus, the institutional impact measurement of the tool has been expanded by focusing on additional status groups besides researchers such as students and librarians. Furthermore, the visualization of the data has been completely updated by improving the operability for the user and including new features such as institutional profile pages. In this paper, we describe the datasets for the current excellencemapping.net tool and the indicators applied. Furthermore, the underlying statistics for the tool and the use of the web application are explained. [ABSTRACT FROM AUTHOR]

Human-computer interaction (HCI) is a research field which engages different disciplines, interest groups and communities, and which has emerged in different countries at different times. To understand how the HCI research community has evolved in Brazil, this paper applies data and visual analytics to its main conference series, the Brazilian Symposium on Human Factors in Computing Systems, henceforth IHC. We have explored the metadata of all 340 full papers published in the 14 editions of IHC. Our goal was to investigate the evolution of the Brazilian HCI community so we can raise the level of 'self-knowledge' and thus discuss strategies that can further help develop this research community. From our analysis, we could understand more deeply the authorship profile of our community and how it has changed over time, the co-authorship networks evolution, the prominent institutions and states, the reference profile and the research topics over time. We hope that this paper will contribute to inspire other scientific communities to analyze themselves, and encourage their own discussions. [ABSTRACT FROM AUTHOR]

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 2000-2004 and 2005-2009. 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. [ABSTRACT FROM AUTHOR]

Based on the original data of 100,275 SSCI indexed papers in the field of economics in 2009-2014, this work applied scientometrics and network analysis methods to study the funding pattern of funding ratio, impacts, indices' relationship and collaboration structure in major countries/territories. Results show that, unlike the notable standing of economics, the global funding ratio of economics in 2009-2014 is just 8.3 %, much lower than the average level of social sciences. Although USA seems to be far ahead in the innovation of economics, the coverage of its science funding has been not widespread. By contrast, the funding ratio of China ranks highest, but the effect of funding needs to be strengthened. We observe an approximate power-law relationship among three basic measures of funded economics papers, including citations, total numbers and h-indexes. The cooperation researches in economics present a key structure of three main components: USA as the central part, a core group of Asia Pacific and another core group of Europe. The collaboration pattern of continents is largely based on the connection between Europe and USA. [ABSTRACT FROM AUTHOR]

We report progress on new developments in the breakthrough paper indicator, which allows early selection of a small group of publications which may become potential breakthrough candidates based on dynamics of publication citations and certain qualitative characteristics of citations. We used a quantitative approach to identify typical citation patterns of highly cited papers. Based on these analyses, we propose two forecasting models to select groups of breakthrough paper candidates that exceed high citation thresholds five years post-publication. Here we study whether interdisciplinarity in the subject categories or geographical diversity serve as possible measures to improve ranking of breakthrough paper candidates. We found that ranked geographical diversities of known breakthrough papers have equal or better ranks than corresponding citations ranks. This allows us to apply additional filtering for better identifications of breakthrough candidates. We studied several interdisciplinarity indices, including richness, Shannon index, Simpson index, and Rao-Stirling-Porter index. We did not find any correlations between citation ranks and ranked interdisciplinarity indices. [ABSTRACT FROM AUTHOR]

Despite their important position in the research environment, there is a growing theoretical uncertainty concerning what research metrics indicate (e.g., quality, impact, attention). Here we utilize the same tools used to study latent traits like Intelligence and Personality to get a quantitative understanding of what over 20 common research metrics indicate about the papers they represent. The sample is all of the 32,962 papers PLoS published in 2014, with results suggesting that there are at least two important underlying factors, which could generally be described as Scientific Attention/Discussion (citations), General Attention/Discussion (views, tweets), and potentially Media Attention/Discussion (media mentions). The General Attention metric is correlated about .50 with both the Academic and Media factors, though the Academic and Media attention are only correlated with each other below .05. The overall best indicator of the dataset was the total lifetime views on the paper, which is also probably the easiest to game. The results indicate the need for funding bodies to decide what they value and how to measure it (e.g., types of attention, quality). [ABSTRACT FROM AUTHOR]

Human–computer interaction (HCI) has become an important area for designers and developers worldwide, and research activities set in national cultural contexts addressing local challenges are often needed in industry and academia. This study explored HCI research in the Nordic-Baltic countries using bibliometric methods. The results show that the activity varies greatly across the region with activities dominated by Finland, Sweden, and Denmark, even when adjusting for differences in population size and GDP. Research output variations were larger for the top-tier conferences compared to entry-tier conferences and journals. Locally hosted conferences were associated with local increases in research activity. HCI research longevity appears to be an indicator of research maturity and quantity. HCI researchers typically collaborated either with colleagues within the same institution or with researchers from countries outside the Nordic-Baltic region such as US and the UK. There was less collaboration between national and Nordic-Baltic partners. Collaboration appeared especially prevalent for top-tier conference papers. Top-tier conference papers were also more frequently cited than regional-tier and entry-tier conferences, yet journal articles were cited the most. One implication of this study is that the HCI research activity gaps across the Nordic-Baltic countries should be narrowed by increasing the activity in countries with low research outputs. To achieve this, first-time authors could receive guidance through collaborations with experienced authors in the same institution or other labs around the world. More conferences could also be hosted locally. Furthermore, journals may be more effective than conferences if the goal is to accumulate citations. [ABSTRACT FROM AUTHOR]

Percentiles are statistics pointing to the standing of a paper's citation impact relative to other papers in a given citation distribution. Percentile Ranks (PRs) often play an important role in evaluating the impact of researchers, institutions, and similar lines of study. Because PRs are so important for the assessment of scholarly impact, and because citations differ greatly across time and fields, various percentile approaches have been proposed to time- and field-normalize citations. Unfortunately, current popular methods often face significant problems in time- and field-normalization, including when papers are assigned to multiple fields or have been published by more than one unit (e.g., researchers or countries). They also face problems for estimating citation counts for pre-defined PRs (e.g., the 90th PR). We offer a series of guidelines and procedures that, we argue, address these problems and others and provide a superior means to make the use of percentile methods more accurate and informative. In particular, we introduce two approaches, CP-IN and CP-EX, that should be preferred in bibliometric studies because they consider the complete citation distribution and can be accurately interpreted. Both approaches are based on cumulative frequencies in percentages (CPs). The paper further shows how bar graphs and beamplots can present PRs in a more meaningful and accurate manner. [ABSTRACT FROM AUTHOR]

Rheumatology is a broad research area with an extensive background in scientific publications. Thus, the present study aims to identify the highly cited papers in Rheumatology research field, analyzing some aspects such as the documents distribution by years, journals, authors, institutions and countries. Furthermore, a conceptual evolution and a co-word analysis have been performed. In order to carry out this study, the H-Classics methodology, based on widely used H-index, has been used. A total of 317 highly cited papers have been detected from a total amount of 103.175 documents (articles and reviews) indexed in the Rheumatology category of the Web of Science database, from the period 1945-2016. As a result, it is obtained that Arthritis and Rheumatism is the journal with the highest number of documents, with more than half of detected documents. Professor Emery, from the University of Leeds (UK), and professor Felson, from the Boston University (USA), are the authors with more highly cited papers. The University of California (USA) and the University of Stanford (USA) are the main institutional contributors. USA is the leading producer, with more than half of the highly cited papers, but it is interesting to highlight the position reached by Peoples R. China, Mexico and, South Africa when an adjustment index based in the GDP per capita is applied. Osteo-arthritis and monoclonal antibody are the leader topics of this set of documents. The present study shows a useful insight into the development and evolution of the Rheumatology research field, revealing actors that have made the most significant research contribution to its development. [ABSTRACT FROM AUTHOR]

In course of the organization of Workshop III entitled "Cited References Analysis Using CRExplorer" at the International Conference of the International Society for Scientometrics and Informetrics (ISSI2021), we have prepared three reference publication year spectroscopy (RPYS) analyses: (i) papers published in Journal of Informetrics; (ii) papers regarding the topic altmetrics; and (iii) papers published by Ludo Waltman (we selected this researcher because he received the Derek de Solla Price Memorial Medal during the ISSI2021 conference). The first RPYS analysis has been presented live at the workshop and the second and third RPYS analyses have been left to the participants for undertaking after the workshop. Here, we present the results for all three RPYS analyses. The three analyses have shown quite different seminal papers with a few overlaps. Many of the foundational papers in the field of scientometrics (e.g., distributions of publications and citations, citation network and co-citation analyses, and citation analysis with the aim of impact measurement and research evaluation) were retrieved as seminal papers of the papers published in Journal of Informetrics. Mainly papers with discussions of the deficiencies of citation-based impact measurements and comparisons between altmetrics and citations were retrieved as seminal papers of the topic altmetrics. The RPYS analysis of the paper set published by Ludo Waltman mainly retrieved papers about network analyses, citation relations, and citation impact measurement. [ABSTRACT FROM AUTHOR]

The distribution of the number of academic publications against citation count for papers published in the same year is remarkably similar from year to year. We characterise the shape of such distributions by a 'width', $$\sigma ^2$$ , associated with fitting a log-normal to each distribution, and find the width to be approximately constant for publications published in different years. This similarity is not surprising, after all, why would papers in a given year be cited more than another year? Nevertheless, we show that simple citation models fail to capture this behaviour. We then provide a simple three parameter citation network model which can reproduce the correct width over time. We use the citation network of papers from the hep-th section of arXiv to test our model. Our final model reproduces the data's observed 'width' when around 20 % of the citations in the model are made to recently published papers in the entire network ('global information'). The remaining 80 % of citations are made using the references from these papers' bibliographies ('local searches'). We note that this is consistent with other studies, though our motivation to achieve the above distribution with time is very different. Finally, we find that, in the citation network model, varying the number of papers referenced by a new publication is important as it alters the parameters in the model which are fitted to the data. This is not addressed in current models and needs further work. [ABSTRACT FROM AUTHOR]

Research and development are central to economic growth, and a key challenge for countries of the global South is that their research performance lags behind that of the global North. Yet, among Southern researchers, a few significantly outperform their peers and can be styled research "positive deviants" (PDs). In this paper we ask: who are those PDs, what are their characteristics and how are they able to overcome some of the challenges facing researchers in the global South? We examined a sample of 203 information systems researchers in Egypt who were classified into PDs and non-PDs (NPDs) through an analysis of their publication and citation data. Based on six citation metrics, we were able to identify and group 26 PDs. We then analysed their attributes, attitudes, practices, and publications using a mixed-methods approach involving interviews, a survey and analysis of publication-related datasets. Two predictive models were developed using partial least squares regression; the first predicted if a researcher is a PD or not using individual-level predictors and the second predicted if a paper is a paper of a PD or not using publication-level predictors. PDs represented 13% of the researchers but produced about half of all publications, and had almost double the citations of the overall NPD group. At the individual level, there were significant differences between both groups with regard to research collaborations, capacity development, and research directions. At the publication level, there were differences relating to the topics pursued, publication outlets targeted, and paper features such as length of abstract and number of authors. [ABSTRACT FROM AUTHOR]

This study is intended to facilitate fair research evaluations in economics. Field- and time-normalisation of citation impact is the standard method in bibliometrics. Since citation rates for journal papers differ substantially across publication years and Journal of Economic Literature classification codes, citation rates should be normalised for the comparison of papers across different time periods and economic subfields. Without normalisation, both factors that are independent of research quality might lead to misleading results of citation analyses. We apply two normalised indicators in economics, which are the most important indicators in bibliometrics: (1) the mean normalised citation score (MNCS) compares the citation impact of a focal paper with the mean impact of similar papers published in the same economic subfield and publication year. (2) PPtop 10 % is the share of papers that belong to the 10% most cited papers in a certain subfield and time period. Since the MNCS is based on arithmetic averages despite skewed citation distributions, we recommend using PPtop 10 % for fair comparisons of entities in economics. In this study, we apply the normalisation methods to 294 journals (including normalised scores for 192,524 papers). We used the PPtop 10 % results for assigning the journals to four citation impact classes. Seventeen journals have been identified as outstandingly cited. Two journals, Quarterly Journal of Economics and Journal of Economic Literature, perform statistically significantly better than all other journals. Thus, only two journals can be clearly separated from the rest in economics. [ABSTRACT FROM AUTHOR]

Recently, the integrated impact indicator (I3) was introduced where citations are weighted in accordance with the percentile rank class of each publication in a set of publications. I3 can also be used as a field-normalized indicator. Field-normalization is common practice in bibliometrics, especially when institutions and countries are compared. Publication and citation practices are so different among fields that citation impact is normalized for cross-field comparisons. In this study, we test the ability of the indicator to discriminate between quality levels of papers as defined by Faculty members at F1000Prime. F1000Prime is a post-publication peer review system for assessing papers in the biomedical area. Thus, we test the convergent validity of I3 (in this study, we test I3/N—the size-independent variant of I3 where I3 is divided by the number of papers) using assessments by peers as baseline and compare its validity with several other (field-normalized) indicators: the mean-normalized citation score, relative-citation ratio, citation score normalized by cited references, characteristic scores and scales, source-normalized citation score, citation percentile, and proportion of papers which belong to the x% most frequently cited papers (PPtop x%). The results show that the PPtop 1% indicator discriminates best among different quality levels. I3 performs similar as (slightly better than) most of the other field-normalized indicators. Thus, the results point out that the indicator could be a valuable alternative to other indicators in bibliometrics. [ABSTRACT FROM AUTHOR]

This study explores the patterns of exchange of research knowledge among Education Research, Cognitive Science, and what we call "Border Fields." We analyze a set of 32,121 articles from 177 selected journals, drawn from five sample years between 1994 and 2014. We profile the references that those articles cite, and the papers that cite them. We characterize connections among the fields in sources indexed by Web of Science (WoS) (e.g., peer-reviewed journal articles and proceedings), and connections in sources that are not (e.g., conference talks, chapters, books, and reports). We note five findings—first, over time the percentage of Education Research papers that extensively cite Cognitive Science has increased, but the reverse is not true. Second, a high percentage of Border Field papers extensively cite and are cited by the other fields. Border Field authors' most cited papers overlap those most cited by Education Research and Cognitive Science. There are fewer commonalities between Educational research and Cognitive Science most cited papers. This is consistent with Border Fields being a bridge between fields. Third, over time the Border Fields have moved closer to Education Research than to Cognitive Science, and their publications increasingly cite, and are cited by, other Border Field publications. Fourth, Education Research is especially strongly represented in the literature published outside those WoS-indexed publications. Fifth, the rough patterns observed among these three fields when using a more restricted dataset drawn from the WoS are similar to those observed with the dataset lying outside the WoS, but Education Research shows a far heavier influence than would be indicated by looking at WoS records alone. [ABSTRACT FROM AUTHOR]

For a recent commentary in Nature, Ioannidis et al. (Nature 561(7722):167-169, 2018) searched the Scopus database and identified those "hyperprolific" authors who have published more than one paper every 5 days. The 265 authors who belong to this very productive class contribute disproportionately to the archive. We show the relationship between paper productivity (annual number of papers) and usefulness of research (annual number of papers which belong to the 1% most frequently cited in the corresponding subject categories and publication years) for 160,108 researchers. Based on our results, we suggest that the identification of "hyperprolific" authors should consider not only quantity, but also the usefulness of research activities (measured in terms of citations). [ABSTRACT FROM AUTHOR]

Altmetrics indices are increasingly applied to measure scholarly influence in recent years because they can reflect the influence of research outputs more timely comparing with traditional measurements. Simultaneously, artificial intelligence (AI), as an emerging interdiscipline, has a rapid development in these years. Traditional indices can't reflect the influence of the AI research outputs quickly, thus more timely altmetrics indices are needed. In this paper, we conduct four studies about altmetrics indices and AI research outputs based on the datasets collected from Altmetric.com and Scopus database. First, we provide a review of the research status in the AI field. Second, we show the AI researches that attracted the most attention. Third, we demonstrate the general effectiveness of altmetrics indices in the AI field. Last, we examine the effectiveness of altmetrics indices for different levels of AI journal papers and AI conference papers. Our results indicate that there is a rapid increase of AI publications and the public has paid more attention to AI research outputs since 2011. It is found that altmetrics indices are effective to discriminate highly cited publications and publications whose citation counts increase quickly. Among all Altmetric sub-indicators, Number of Mendeley readers is the most effective. Moreover, the results indicate that altmetrics indices are more effective in high levels of AI journal papers and AI conference papers. The main contribution of this paper is investigating the effectiveness of altmetrics indices from the perspective of different levels of publications. This study lays the foundation for further investigations about effectiveness of altmetrics indices from new perspectives, and it has important implication for the studies about the impact of social media on the scientific community. [ABSTRACT FROM AUTHOR]

Many believe that the quality of a scientific publication is as good as the science it cites. However, quantifications of how features of reference lists affect citations remain sparse. We examined seven numerical characteristics of reference lists of 50,878 research articles published in 17 ecological journals between 1997 and 2017. Over this period, significant changes occurred in reference lists' features. On average, more recent papers have longer reference lists and cite more high Impact Factor papers and fewer non-journal publications. We also show that highly cited articles across the ecological literature have longer reference lists, cite more recent and impactful references, and include more self-citations. Conversely, the proportion of 'classic' papers and non-journal publications cited, as well as the temporal span of the reference list, have no significant influence on articles' citations. From this analysis, we distill a recipe for crafting impactful reference lists, at least in ecology. [ABSTRACT FROM AUTHOR]

The history of AI in economics is long and winding, much the same as the evolving field of AI itself. Economists have engaged with AI since its beginnings, albeit in varying degrees and with changing focus across time and places. In this study, we have explored the diffusion of AI and different AI methods (e.g., machine learning, deep learning, neural networks, expert systems, knowledge-based systems) through and within economic subfields, taking a scientometrics approach. In particular, we centre our accompanying discussion of AI in economics around the problems of economic calculation and social planning as proposed by Hayek. To map the history of AI within and between economic sub-fields, we construct two datasets containing bibliometrics information of economics papers based on search query results from the Scopus database and the EconPapers (and IDEAs/RePEc) repository. We present descriptive results that map the use and discussion of AI in economics over time, place, and subfield. In doing so, we also characterise the authors and affiliations of those engaging with AI in economics. Additionally, we find positive correlations between quality of institutional affiliation and engagement with or focus on AI in economics and negative correlations between the Human Development Index and share of learning-based AI papers. [ABSTRACT FROM AUTHOR]

Research that integrates the social and natural sciences is vital to address many societal challenges, yet is difficult to arrange, conduct, and disseminate. This paper compares diffusion of the research supported by a unique U.S. National Science Foundation program on Human and Social Dynamics ('HSD') with a matched group of heavily cited papers. We offer a measure of the distance of cites between the Web of Science Category ('WoSC') in which a publication appears and the WoSC of the journal citing it, and find that HSD publications are cited more distantly than are comparison publications. We provide another measure-citation velocity-finding that HSD publications are cited with similar lag times as are the comparison papers. These basic citation distance and velocity measures enrich analyses of research knowledge diffusion patterns. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

On January 1, 2015, the Republic of Armenia joined the (Russian-led) Eurasian Economic Union (EAEU) and actually refrained from entering into the alternative Association Agreement with the European Union (EU). Nevertheless, despite the prevalence of historic ties with the scientific community of the EAEU member-states and some push towards that direction, Armenian researchers demonstrate a certain scientific autonomy, which is expressed in numerous international scientific collaborations with researchers from many European countries. This paper proposes a bibliometric analysis of the international scientific collaboration between (i) Armenia and EU countries, and (ii) Armenia and EAEU countries, based on the papers indexed by the Web of Science Core Collection database and the Russian Science Citation Index database. Results indicate that the international collaboration with researchers from countries of both blocks gradually grows, displaying similarities and differences. Globally, Armenian researchers seem to collaborate more with researchers from EU countries rather than EAEU countries. Despite this, individual collaborations with Russia continue to prevail over those with other individual European countries, primarily Germany. Finally, it has been noted that "megaprojects" significantly influence the scientific collaborations between Armenian and foreign researchers. [ABSTRACT FROM AUTHOR]

The understanding of the inner workings of a research community is essential to evaluate the impact of an author as well as to decide where and how to publish results. One of the key metrics is the number of citations that a publication receives. In parallel, information security is now a key and strategic area, partially fueled by the advent of the Internet of Things (IoT) and the need of pursuing cybercriminals by using digital forensics techniques. Therefore, this paper analyzes several factors influencing the number of citations in the domain of information security, such as differences between journal and conference publications, or the impact of the number of pages and the length of the abstract. To obtain quantitative results, we investigated papers of six sub-disciplines, i.e., anonymity and privacy, cryptography, information hiding, IoT and Cyber-Physical System security, digital forensics and incident response, and network security. For each sub-domain, we used metadata of 5000 publications collected from IEEE-Xplore. Results indicate some clear behaviors, for instance, papers tend to receive more citations when their abstract is longer and the number of references positively influences the performance of the work. [ABSTRACT FROM AUTHOR]

This work presents a new approach for analysing the ability of existing research metrics to identify research which has strongly influenced future developments. More specifically, we focus on the ability of citation counts and Mendeley reader counts to distinguish between publications regarded as seminal and publications regarded as literature reviews by field experts. The main motivation behind our research is to gain a better understanding of whether and how well the existing research metrics relate to research quality. For this experiment we have created a new dataset which we call TrueImpactDataset and which contains two types of publications, seminal papers and literature reviews. Using the dataset, we conduct a set of experiments to study how citation and reader counts perform in distinguishing these publication types, following the intuition that causing a change in a field signifies research quality. Our research shows that citation counts work better than a random baseline (by a margin of 10%) in distinguishing important seminal research papers from literature reviews while Mendeley reader counts do not work better than the baseline. [ABSTRACT FROM AUTHOR]

The Keeling curve has become a chemical landmark, whereas the papers by Charles David Keeling about the underlying carbon dioxide measurements are not cited as often as can be expected against the backdrop of his final approval. In this bibliometric study, we analyze Keeling's papers as a case study for under-citedness of climate change publications. Three possible reasons for the under-citedness of Keeling's papers are discussed: (1) The discourse on global cooling at the starting time of Keeling's measurement program, (2) the underestimation of what is often seen as 'routine science', and (3) the amount of implicit/informal citations at the expense of explicit/formal (reference-based) citations. Those reasons may have contributed more or less to the slow reception and the under-citedness of Keeling's seminal works. [ABSTRACT FROM AUTHOR]

The present study sought to examine the trend and impact of international collaboration in scientific research in Vietnam during the period after the introduction of the a reform policy and the normalization of relations with the United States. Using the Thomson Reuters' Web of Science data (2001-2015) we found that 77% of Vietnam's scientific output ( n = 18,044 papers) involved international collaborations, with the United States and Japan researchers being the most frequent partners. The proportion of international collaborations has decreased slightly over time at the expense of an increased rate of domestic collaborations. The rate of growth in Vietnam's scientific output was 17% per annum, and three-quarters of the growth was associated with international collaborations rather than purely domestic production. Moreover, internationally coauthored papers received twice the average citation as domestic papers. Of note, papers with overseas corresponding author had higher citation rate than papers with domestic corresponding author. These data suggest that the vast majority of scientific papers from Vietnam was attributable to international collaboration, and this had a positive impact on the quality and visibility of Vietnam science. The data also indicate that Vietnam is in the growth phase of building up research capacity. [ABSTRACT FROM AUTHOR]

Over the past 30 years, the research behavior of Chinese scholars has continually evolved. This paper studied the citing behavior of Chinese scholars by employing three indicators of citation concentration from the perspective of citation breadth analysis. All the citations from 2,338,033 papers from the Chinese Citation Database (1979-2008) covering four disciplines-Chemistry; Clinical Medicine; Library, Information and Archival Science; and Chinese Literature and World Literature-were analyzed. Empirical results show a general weakening tendency towards citation concentration: (1) decreasing percentage of uncited published papers within a given year; (2) a higher percentage of papers required to account for the same proportion of citation than before; and (3) the steady decline in the Herfindahl-Hirschman index (HHI) of citation distribution. All three measures indicate a decline in citing concentration or an increase in citation breadth. This phenomenon may be the result of increased access to materials, perhaps because of the ease with which scholarly materials can be accessed through the Internet. [ABSTRACT FROM AUTHOR]

The paper aims to build the genealogy of the literature on Internationalization of Family Business (IFB) identifying the 'fathers' (the most important papers in the field), 'ancestors' (those on which the fathers have been built on), and 'descendants' (the most recent publications and topics) of the research field. Results originate from a complete database on which we used a bibliometric mixed-method approach by sequentially employing citation analysis, co-citation analysis, and bibliographic coupling. Our analysis enriches the academic debate on IFB with more understanding of the field's knowledge structure (origins, theoretical roots, and developments), meanwhile proposing a sequential use of different bibliometric methods and providing a methodological contribution. [ABSTRACT FROM AUTHOR]

Under the Excellence Initiative, a number of Clusters of Excellence in Germany have been supported since 2006 and 2007-including each a limited number of cooperating institutions. The aim of the present study is to investigate whether support for Clusters of Excellence since 2006 and 2007 is reflected in bibliometric network data. For this purpose, a comparison is made between network data in the period before support started (2003-2005) and in the period after support started (2009-2011). For these two periods, a co-authorship network is generated (based on the funded institutions). This is based on publications which are among the 1 % most frequently cited publications in their respective fields and publication year and which have at least one author from Germany. As the results show, the outcomes this yields for life sciences and natural sciences differ from each other. Whereas natural sciences display an effect of establishment of Clusters of Excellence on the bibliometric networks, this was not true of life sciences. After establishment of the Clusters of Excellence, the network in natural sciences not only contained more institutions of a Cluster of Excellence, but these institutions were distributed across fewer bibliometric clusters in the network than before establishment. In other words the structure of the Clusters of Excellence was better reflected in the network. [ABSTRACT FROM AUTHOR]

Studying the history of research fields by analyzing publication records and topical and/or keyword searches with reference publication year spectroscopy (RPYS) has been introduced as a powerful tool to identify the corresponding root publications. However, for some research fields (e.g., rather new and interdisciplinary fields) like solar energy meteorology, encompassing such research fields via a keyword- or topic-based search query is not feasible to get a reasonably exhaustive publication set. Therefore, we apply its variant RPYS-CO to all publications co-cited with two highly important marker papers, using the cited references explorer for inspecting the RPYS-CO results. We obtain two lists of seminal papers, which are able to adequately tell us the story of solar energy meteorology up to the 1990s, respectively in its subfield using satellite-based methods for solar irradiance estimation even to very recent years. Consequently, we recommend this method to gain valuable insights in (new) research fields. [ABSTRACT FROM AUTHOR]

Governments typically formulate sets of policies to guide the direction of scientific research. And the possible effects of these policies on scientific research have been explored. However, there is limited literature reflecting how policy information is incorporated and concerned by scientific research. In this research, we explore policy usages in scientific research by analyzing the occasions when these policies are mentioned. Taking China's S&T evaluation policies as a specific case, we analyzed mentions of these policies in terms of velocity, strength, usage priority, usage variations, and usage intentions. From these perspectives, we found that the strength and velocity of mentions have consistently increased over the years. Additionally, researchers have tended to focus more on policies issued by senior agencies or by multiple agencies. Further, there are great variations in policy sensitivity across institutions and disciplines, with universities actively reacting to policies and social science research showing remarkable policy take-up. Last, these policies are often mentioned in the analysis section of papers alongside the major functionality of policy content reference. However, the locations and specific usages of the policies do not follow a fixed model. Overall, the quantitative side of our analysis reveals the diverse policy usages in scientific research activity. These new insights sharpen our perceptions of how policies pertain to and are used by scientific research in real-world settings. [ABSTRACT FROM AUTHOR]

This paper seeks to build upon the previous literature on gender aspects in research collaboration and knowledge diffusion. Our approach adds the meme inheritance notion to traditional citation analysis, as we investigate if scientific memes are inherited differently from gendered authorship. Since authors of scientific papers inherit knowledge from their cited authors, once authorship is gendered we are able to characterize the inheritance process with respect to the frequencies of memes and their propagation scores depending on the gender of the authors. By applying methods that enable the gender disambiguation of authors, missing data on the gender of citing and cited authors is dealt with. Our empirically based approach allows for investigating the combined effect of meme inheritance and gendered transmission. Results show that scientific memes do not spread differently from either male or female cited authors. Likewise, the memes that we analyse were not found to propagate more easily via male or female inheritance. [ABSTRACT FROM AUTHOR]

An outcome of nuclear safety research (NSR) done by JAERI (Japan Atomic Energy Research Institute) was case studied by the bibliometric method. (1) For LOCA (loss-of-coolant accident) a domestic share of JAERI in monoclinic research paper was 63% at the past (20) 1978–1982 but was decreased to 40% at the present 1998–2002. For co-authored papers a domestic share between JAERI and PS (public sectors) was zero at past (20) but increased to 4% at the present. Research cooperation is active between Tokyo University and JAERI or between JAERI and Nagoya University. (2) It is revealed that LOCA outputs born by NSR-JAERI reflected partly to those of the Safety Licensing Guidelines, however, a share of NSR-JAERI could not determined due to the lack of necessary information in the Guideline. [ABSTRACT FROM AUTHOR]

The order in which authors of a scientific paper place their names on the byline follows in many research fields some implicit rules. In most fields, the first author is considered to be the one who contributed most to the intellectual effort described in the paper. Additionally, the last author is normally the most senior researcher and in many situations the contribution to the paper is more indirect. In this manuscript, we intend to analyse the evolution of the positions of computer science (CS) researchers on the bylines of scientific papers throughout their careers. In particular, this bibliometic study considers the Association for Computing Machinery (ACM) Fellows (the most prestigious members) that present a long and rich publication record. Our hypothesis is that young CS authors tend to have their names placed in the first positions of the bylines, while senior CS researchers are often considered as last authors. Several statistical analyses were conducted by using biblometric data collected from ACM Fellows and other CS researchers. Overall, the obtained results do confirm our initial hypothesis. [ABSTRACT FROM AUTHOR]

A scientometric analysis of funded scientometric and bibliometric research from 2011 to 2021 is presented in this paper. Using Web of Science, we analyzed 2810 domain-relevant papers (DRP) and 1040 methodologically relevant papers (MRP). A number of standard scientometric parameters have been examined in the study, including the relative growth rate (RGR), the doubling time (DT), the activity index (AI), the average citations per paper (ACCP), and the h-index. This study provides a comprehensive analysis of the parameters associated with the most productive funding agencies, international country collaboration patterns, top journals, most productive institutions, trends in the field, as well as emerging themes. In this paper, we analyze scientometric and bibliometric research funding by nature of study, which is the first study of its kind. [ABSTRACT FROM AUTHOR]

Using the participation in peer reviewed publications of all doctoral students in Quebec over the 2000-2007 period, this paper provides the first large scale analysis of their research effort. It shows that PhD students contribute to about a third of the publication output of the province, with doctoral students in the natural and medical sciences being present in a higher proportion of papers published than their colleagues of the social sciences and humanities. Collaboration is an important component of this socialization: disciplines in which student collaboration is higher are also those in which doctoral students are the most involved in peer-reviewed publications. In terms of scientific impact, papers co-signed by doctorate students obtain significantly lower citation rates than other Quebec papers, except in natural sciences and engineering. Finally, this paper shows that involving doctoral students in publications is positively linked with degree completion and ulterior career in research. [ABSTRACT FROM AUTHOR]

Bibliometric research assessment has matured into a quantitative phase using more meaningful measures and analogies. In this paper, we propose a thermodynamic analogy and introduce what are called the energy, exergy and entropy terms associated with a bibliometric sequence. This can be displayed as time series (variation over time), or in event terms (variation as papers are published) and also in the form of phase diagrams (energy-exergy-entropy representations). It is exergy which is the most meaningful single number scalar indicator of a scientist's performance while entropy then becomes a measure of the unevenness (disorder) of the publication portfolio. [ABSTRACT FROM AUTHOR]

This study presents a historical overview of the International Conference on Human Robot Interaction (HRI). It summarizes its growth, internationalization and collaboration. Rankings for countries, organizations and authors are provided. Furthermore, an analysis of the military funding for HRI papers is performed. Approximately 20% of the papers are funded by the US Military. The proportion of papers from the US is around 65% and the dominant role of the US is only challenged by the strong position of Japan, in particular by the contributions by ATR. [ABSTRACT FROM AUTHOR]

First coined in 2006, the term 'crowdsourcing' began to appear as a concept in academic literature around 2009. Since then academic research on this topic has been showing a rising trend, most prominently in the field of computer science and its subfields. Analysis of the types of motivations for using crowdsourcing shows that extrinsic motivations are mentioned more often in the literature, compared to intrinsic ones. This serves to establish the perception of crowdsourcing as a research method for gaining robust insight on an issue, rather than as a recreational activity for personal development. Finally, the findings of this study reveal that China is emerging as the main funder and producer of papers on crowdsourcing. [ABSTRACT FROM AUTHOR]