Science Subject Categories Research Articles

Which are the influential publications in the Web of Science subject categories over a long period of time? CRExplorer software used for big-data analyses in bibliometrics

What are the landmark papers in scientific disciplines? Which papers are indispensable for scientific progress? These are typical questions which are of interest not only for researchers (who frequently know the answers – or guess to know them) but also for the interested general public. Citation counts can be used to identify very useful papers since they reflect the wisdom of the crowd – in this case, the scientists using published results for their research. In this study, we identified with recently developed methods for the program CRExplorer landmark publications in nearly all Web of Science subject categories (WoS-SCs). These are publications which belong more frequently than other publications during the citing years to the top-1‰ in their subject area. As examples, we show the results of five subject categories: ‘Information Science & Library Science’, ‘Computer Science, Information Systems’, ‘Computer Science, Software Engineering’, ‘Psychology, Social’ and, ‘Chemistry, Physical’. The results of the other WoS-SCs can be found online at http://crexplorer.net . An analyst of the results should keep in mind that the identification of landmark papers depends on the used methods and data. Small differences in methods and/or data may lead to other results.

Analysis of Percentiles of Computer Science, Theory and Methods Journals CiteScore Versus Impact Factor


 
 
 Impact factor (Web of Science, Clarivate Analytics) and CiteScore (Scopus, Elsevier) are the two leading metrics for journal evaluation, assessment and ranking. The relationship between the two is now established, using their respective percentile in this paper for 105 journal in the Computer science, theory and methods (CSTM) subject category. The available studies did not consider the quartile comparison of the journal percentiles of the two database (Scopus and Science Citation Index expanded). The mean impact factor and CiteScore are 2.08 and 2.67 respectively. Pearson correlation coefficient between the impact factor and CiteScore is (0.919, p = 0.000) and between their respective journal percentiles is (r = 0.804, p = 0.000). Analysis of variance revealed that the means of the impact factor and CiteScore of the 105 CSTM journals are the same (F = 3.64, P = 0.058) but different (F = 38.94, P = 0.00) for their respective percentiles. The median test contradicts the ANOVA as the medians of impact factor and CiteScore are different at 0.05 level of significance. The median journal percentiles are the same for only 2 journal titles. The median journal percentile (SCIE) is greater than the median journal percentile (Scopus) for 5 journal titles and less than the median journal percentile (Scopus) for 98 journal titles. The same result was obtained when the percentiles were converted to quartiles, but in this case, the median journal quartiles are the same for 37 journal titles. The median journal quartile (SCIE) is greater than the median journal quartile (Scopus) for 67 journal titles and less than the median journal quartile (Scopus) in only one journal title. Only 37 (35 %) journals are in the same quartile of the two metrics. Caution is recommended in journal evaluation as conflicting different results can be obtained using the same metric.
 
 

Arts and Humanities and the others: Why can’t we measure arts and humanities

The use of numbers (publications and citations) to evaluate research/er performances are widespread since ease of use. However, disciplinary differences must be considered to evaluate research/ers accurately without misjudgments in tenures and incentives. The most different filed from others in terms of publications and citation patterns is Arts & Humanities. The main aim of this study is to reveal the main differences between Arts & Humanities and the other fields by considering publications, citations, and collaboration. For this aim, the main statistics for 59,728,700 papers published between 1980-2018 are gathered from InCites in terms of the 251 Web of Science subject categories. The data confirmed that Arts & Humanities is considerably different from other fields. We showed the degree of these differences using statistical measures. The huge difference found out that underline the indispensability for evaluating Arts & Humanities separately from the others.

Bibliometric and mapping of top papers in the subject category of green and sustainable science and technology based on ESI

Based on the Essential Science Indicators database, this study analyzed 2,138 top papers in the subject category of Green & Sustainable Sci- ence & Technology database from 2008 to 2018, including 2,130 highly cited papers and 61 hot papers. Results showed there are total 19 Web of Science subject categories, all paper written in English, were from 6,228 authors, 2,019 organizations and 94 countries/territories, listed in 30 journals in the field. Top 4 core journals with higher impact factor ranked as Renewable sustainable energy reviews, Journal of cleaner production, Renewable energy, Green chemistry. Based on the analysis of network map of VOSviewer, there is cooperation for authors, organizations and countries or regions. The analysis of keywords showed that the researches were separated into nine clusters. Therefore, authors can choose their ideal journal with a high impact factor to publish papers in the English language related to this research field.

Measuring the academic reputation through citation networks via PageRank

The objective assessment of the prestige of an academic institution is a difficult and hotly debated task. In the last few years, different types of University Rankings have been proposed to quantify the excellence of different research institutions in the world. Albeit met with criticism in some cases, the relevance of university rankings is being increasingly acknowledged: indeed, rankings are having a major impact on the design of research policies, both at the institutional and governmental level. Yet, the debate on what rankings are {\em exactly} measuring is enduring. Here, we address the issue by measuring a quantitive and reliable proxy of the academic reputation of a given institution and by evaluating its correlation with different university rankings. Specifically, we study citation patterns among universities in five different Web of Science Subject Categories and use the \pr~algorithm on the five resulting citation networks. The rationale behind our work is that scientific citations are driven by the reputation of the reference so that the PageRank algorithm is expected to yield a rank which reflects the reputation of an academic institution in a specific field. Our results allow to quantifying the prestige of a set of institutions in a certain research field based only on hard bibliometric data. Given the volume of the data analysed, our findings are statistically robust and less prone to bias, at odds with ad--hoc surveys often employed by ranking bodies in order to attain similar results. Because our findings are found to correlate extremely well with the ARWU Subject rankings, the approach we propose in our paper may open the door to new, Academic Ranking methodologies that go beyond current methods by reconciling the qualitative evaluation of Academic Prestige with its quantitative measurements via publication impact.

How video articles are cited, the case of JoVE: Journal of Visualized Experiments

Journal of Visualized Experiments (JoVE) is a peer-reviewed journal that publishes video articles. In order to find out about the impact of video articles and how they are used in other journal articles, a random sample of 500 articles that cited at least one JoVE article was drawn and citation content analysis was conducted to find out about reasons for citation, frequency of citation mentions, location of citation and any relation between in-text citation characteristics and times cited. The results showed that JoVE articles are mostly cited for methodological reasons (72.4%) and in method sections of articles (53.2%). The context of 44.1% of citation mentions included phrases such as ‘as previously described’. More than a third (38.8%) of citations to JoVE articles were self-citations. JoVE articles that were self-cited were more likely to have a larger number of citation mentions, be cited for different reasons and in different sections of citing articles. They were also more likely to have more authors. The majority of the articles (75.6%) were mentioned only once in the citing articles. The median impact factor (MIF) of the journals of citing articles was higher than MIF of any Web of Science subject category, indicating that the citing articles were mostly from journals with relatively high impact factors. Overall, JoVE articles play an important role in transparency and transfer of methodologies and processes in research.

Identification of research communities in cited and uncited publications using a co-authorship network

Patterns of co-authorship provide an effective means of probing the structures of research communities. In this paper, we use the CiteSpace social network tool and co-authorship data from the Web of Science to analyse two such types of community. The first type is based on the cited publications of a group of highly productive authors in a particular discipline, and the second on the uncited publications of those highly productive authors. These pairs of communities were generated for three different countries—the People’s Republic of China (PRC), the United Kingdom (UK) and the United States of America (USA)—and for four different disciplines (as denoted by Web of Science subject categories)—Chemistry Organic, Engineering Environmental, Economics, and Management. In the case of the UK and USA, the structures of the cited and uncited communities in each of the four disciplines were markedly different from each other; in the case of the PRC, conversely, the cited and uncited PRC communities had broadly similar structures that were characterised by large groups of connected authors. We suggest that this may arise from a greater degree of guest or honorary authorship in the PRC than in the UK or the USA.

Correction and retraction practices in library and information science journals

Retraction of scholarly publications ensures that unqualified knowledge is purged from the scientific community. However, there appears to be little understanding about how this is practiced among library and information science (LIS) journals. Hence, this study investigated the correction and retraction practices of LIS journals. Journals included in the Web of Science’s information science and library science subject category were selected for the study and the characteristics of the articles corrected or retracted in those journals between 1996 and 2016 were examined. Findings show that there were 517 corrections and five retractions in LIS journals during the period. Most of the corrections made to articles in LIS journals were minor while the reasons for article retraction included plagiarism, duplication, irreproducible results and methodological errors. Our findings also reveal that on average it took about 587 days for an article to be retracted while some of the retracted articles continued to be cited after retraction. The study concluded that the average number of errors per correction was lower than what had been observed in medical journals while some of the retracted articles continued to receive positive post-retraction citations. It also recommended the inclusion of a check on the validity of literature cited by authors at the review stage as part of the quality control mechanism by publishers of LIS journals.

Are leaders really leading? Journals that are first in Web of Science subject categories in the context of their groups

This study focuses on journals that lead their Web of Science (WoS) subject category ranking when the usual 2-year window for the Journal Impact Factor (JIF2) is used as the ranking variable, and examines evidence that contradicts their top-ranked position in the context of their group. The source data were obtained from all 177 WoS subject categories in the Science Edition 2015 Journal Citation Reports (JCR). I compared journals in each WoS subject category with leaders in terms of JIF2, number of citable items and number of citations that contribute to the JIF2. Rankings were calculated with alternative metrics (for example, the Journal Impact Factor without self-citations and the eigenfactor), and the minimum reduction in the number of citations that would displace the top-ranked journal from its leading position was also calculated. In addition, the stability of rankings over time, the number of WoS subject categories in which journals are leaders, the publishers that own leading journals, and the percentages of research articles (as opposed to review articles) published in different journals were also studied. In general, leading journals are not necessarily the top-ranked in terms of citations received or the number of citable items they publish. In addition, most leaders maintained their position when other metrics were used instead the JIF2, although rankings based on the eigenfactor were at variance with this finding. The distribution of publishers was highly skewed, with a linear relationship between the cumulative number of publishers owning the top-ranked journal and the cumulative number of WoS subject categories. In only 85 subject categories (48%) the percentage of research articles (not reviews) in the number of citable items was greater than the mean percentage for the subject category. In 31 instances, leaders did not publish any research articles, but only reviews.

Bibliometric Analysis of Ghana Publications in the Science Citation Index Expanded

Ghana is a West African country for which apparently there are limited scientometric studies. The objective of this study was to analyze the Ghanaian contribution to knowledge captured in the Thomson Reuters Science Citation Index Expanded (SCI-EXPANDED) database from 1936 - 2016. The following data were analyzed: document type, the language of publication, publication trend, Web of Science Subject Categories, Journals, international collaboration, institutions, authors, and highly cited articles. Indicators such as the total number of articles, first author articles, and corresponding author articles were applied to compare publication performance for collaborative countries and institutions. Also, number of single institute articles: number of nationally collaborative articles: number of internationally collaborative articles (S : N : I) were also used to compare publication characteristics of institutions in Ghana. Results showed that publication trend increased from 1998 to 2015, with researches focusing on health and medicine. PLoS One was the top productive journal, and the most collaborative country for Ghana articles was the USA. Contributions from the University of Ghana were ranked the top one institution for Ghana articles, and higher citation papers were found in international collaborations. In conclusion, the contribution to knowledge of Ghanaian authors is massive in the areas of public, environmental and occupational health and tropical medicine but the impact factor is higher for immunology, infectious diseases, and microbiology articles. Therefore, Ghanaian authors are encouraged to publish more articles in high impact factor journals with Thomson Reuters Scientific indexing in order to have their researches recognized by the existing international databases.

Cognitive Distances between Evaluators and Evaluees in Research Evaluation: A Comparison between Three Informetric Methods at the Journal and Subject Category Aggregation Level

This article compares six informetric approaches to determine cognitive distances between the publications of panel members and those of research groups in discipline-specific research evaluation. We used data collected in the framework of six completed research evaluations from the period 2009-2014 at the University of Antwerp as a test case. We distinguish between two levels of aggregation – Web of Science subject categories and journals – and three methods: while the barycenter method (2-dimensional) is based on global maps of science, the similarity-adapted publication vector (SAPV) method and weighted cosine similarity (WCS) method (both in higher dimensions) use a full similarity matrix. In total, this leads to six different approaches, all of which are based on the publication profile of research groups and panel members. We use Euclidean distances between barycenters and SAPVs, as well as values of WCS between panel members and research groups as indicators of cognitive distance. We systematically compare how these six approaches are related. The results show that the level of aggregation has minor influence on determining cognitive distances, but dimensionality (two versus a high number of dimensions) has a greater influence. The SAPV and WCS methods agree in most cases at both levels of aggregation on which panel member has the closest cognitive distance to the group to be evaluated, whereas the barycenter approaches often differ. Comparing the results of the methods to the main assessor that was assigned to each research group, we find that the barycenter method usually scores better. However, the barycenter method is less discriminatory and suggests more potential evaluators, whereas SAPV and WCS are more precise.

Establishing interoperability among knowledge organization systems for research management: a social network approach

Knowledge organization systems (KOS) have long been established as a tool to represent organized interpretation of knowledge structures. Various types of KOS such as discipline tree for research projects, subject categories for research publications, and classifications schemes for research patents have been constructed and widely used in R&D contexts. However, the incompatible KOS, together with information proliferation in the Big Data Era, impose great challenges for effective research management. How to facilitate interoperability among heterogeneous research information sources is an important problem to be solved. KOS mapping methods were proposed to provide alternative subject access by establishing equivalence or partial equivalence relationships between classes in different KOS but suffered from “lagging mapping” and “deficient mapping”. This research proposes a social network approach that leverages online social platform information (i.e., research activities and social activities) for KOS mapping. The underlying assumption behind the approach is that “two classes/terms in different KOS are related if their corresponding research objects are connected to similar researchers”. The social network approach leverages social network analysis instead of semantic and structure analysis of metadata information for mapping degree calculation. The approach has been implemented on the largest research social platform in China and successfully realizes mapping between KOS for research management purpose. We conducted mapping between National Natural Science Foundation of China discipline tree and Web of Science subject categories in this study to examine the performance of social network approach.

Can the journal impact factor be used as a criterion for the selection of junior researchers? A large-scale empirical study based on ResearcherID data

Abstract Early in researchers’ careers, it is difficult to assess how good their work is or how important or influential the scholars will eventually be. Hence, funding agencies, academic departments, and others often use the Journal Impact Factor (JIF) of where the authors have published to assess their work and provide resources and rewards for future work. The use of JIFs in this way has been heavily criticized, however. Using a large data set with many thousands of publication profiles of individual researchers, this study tests the ability of the JIF (in its normalized variant) to identify, at the beginning of their careers, those candidates who will be successful in the long run. Instead of bare JIFs and citation counts, the metrics used here are standardized according to Web of Science subject categories and publication years. The results of the study indicate that the JIF (in its normalized variant) is able to discriminate between researchers who published papers later on with a citation impact above or below average in a field and publication year – not only in the short term, but also in the long term. However, the low to medium effect sizes of the results also indicate that the JIF (in its normalized variant) should not be used as the sole criterion for identifying later success: other criteria, such as the novelty and significance of the specific research, academic distinctions, and the reputation of previous institutions, should also be considered.

Agriculture vs. social sciences: subject classification and sociological conceptualization of rural tourism in Scopus and Web of Science

Agriculture and consumptive function of countryside (rural areas) are connected which should be reflected in scientific research. In order to test relationships, we selected the topic of rural tourism (also agritourism, agrotourism, agricultural tourism) considering sociological conceptualization (social sciences, sociology) and methodological approaches of information sciences (bibliometrics, scientometrics) in describing fields of science or scientific disciplines. We ascertained scatter of information in citation databases (Web of Science, Scopus, Google Scholar). Functionalities were evaluated, affecting search precision and recall in information retrieval. We mapped documents to Scopus subject areas as well as Web of Science (WOS) research areas and subject categories, and related publications (journals). Databases do not differ substantially in mapping this topic. Social sciences (including economics or business) occupy by far the most important place. The strongest concentration was found in tourism-related journals (consistent with power laws). Agriculture-related publications are rare, accounting for some 10 % of documents. Interdisciplinarity seems to be weak. Results point to poor inclusion of emerging social topics in agricultural research whereby agriculture may lose out in possible venues of future research.

Measuring the match between evaluators and evaluees: cognitive distances between panel members and research groups at the journal level

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

Global research on air pollution between 2005 and 2014: a bibliometric study

Purpose The purpose of this paper is to analyze research works on air pollution published in 2005-2014 and indexed in Web of Science Core Collection. Design/methodology/approach The data of research publications on “air pollution” from the Web of Science Core Collection database were collected with following search strategy: publications with terms “Air contaminat*”, “Air pollut*”, “pollut* air” or “contaminat* air” in their titles for the period of 2005-2014 were collected. A total of 4,424 articles were published on air pollution during the period of 2005-2014, and the data were used for creation of database in Microsoft Excel for the analysis purpose. Bibliometric analysis techniques were applied wherever necessary. Findings Out of 4,424 articles published on air pollution in different languages, 4,276 articles were in English. The years 2013 and 2014 showed rapid increase in number of articles published, 563 and 638, respectively. The increased number of articles resulted in an increase in number of pages published and references cited in the articles. The articles published in the year 2006 had received more number of citations (12,318), and the average citation per article for the period was 17.59. Environmental Science was the major Web of Science subject category under which a greater number of articles were published. Article entitled as “Health effects of fine particulate air pollution: Lines that connect”, published in Journal of The Air & Waste Management Association by Pope and Dockery (2006), was the highest cited article (1,743) for the period, and the top most active journals that published huge number of articles were Atmospheric Environment and Environmental Health Perspective, with 11.79 per cent of the total articles (4,424) published. Research limitations/implications The findings of the study are limited to the journals covered under Web of Science Core Collection database and articles having the following keywords in their titles: “Air contaminat*”, “Air pollut*”, “pollut* air” or “contaminat* air”. Originality/value This study would be useful to researchers and policy makers to get an insight into the research trends of air pollution for effective decision-making and formulation of new research proposals.

Normalization of Mendeley reader impact on the reader- and paper-side: A comparison of the mean discipline normalized reader score (MDNRS) with the mean normalized reader score (MNRS) and bare reader counts

Abstract For the normalization of citation counts, two different kinds of methods are possible and used in bibliometrics: the cited-side and citing-side normalizations both of which can also be applied in the normalization of “Mendeley reader counts”. Haunschild and Bornmann (2016a) introduced the paper-side normalization of reader counts (mean normalized reader score, MNRS) which is an adaptation of the cited-side normalization. Since the calculation of the MNRS needs further data besides data from Mendeley (a field-classification scheme, such as the Web of Science subject categories), we introduce here the reader-side normalization of reader counts which is an adaptation of the citing-side normalization and does not need further data from other sources, because self-assigned Mendeley disciplines are used. In this study, all articles and reviews of the Web of Science core collection with publication year 2012 (and a DOI) are used to normalize their Mendeley reader counts. The newly proposed indicator (mean discipline normalized reader score, MDNRS) is obtained, compared with the MNRS and bare reader counts, and studied theoretically and empirically. We find that: (i) normalization of Mendeley reader counts is necessary, (ii) the MDNRS is able to normalize Mendeley reader counts in several disciplines, and (iii) the MNRS is able to normalize Mendeley reader counts in all disciplines. This generally favorable result for the MNRS in all disciplines leads to the recommendation to prefer the MNRS over the MDNRS—provided that the user has an external field-classification scheme at hand.

Back to the past: on the shoulders of an academic search engine giant

A study released by the Google Scholar team found an apparently increasing fraction of citations to old articles from studies published in the last 24 years (1990-2013). To demonstrate this finding we conducted a complementary study using a different data source (Journal Citation Reports), metric (aggregate cited half-life), time spam (2003-2013), and set of categories (53 Social Science subject categories and 167 Science subject categories). Although the results obtained confirm and reinforce the previous findings, the possible causes of this phenomenon keep unclear. We finally hypothesize that first page results syndrome in conjunction with the fact that Google Scholar favours the most cited documents are suggesting the growing trend of citing old documents is partly caused by Google Scholar.

Correlation between impact factor and public availability of published research data in Information Science and Library Science journals

Scientists continuously generate research data but only a few of them are published. If these data were accessible and reusable, researchers could examine them and generate new knowledge. Our purpose is to determine whether there is a relationship between the impact factor and the policies concerning open availability of raw research data in journals of Information Science and Library Science (ISLS) subject category from the Web of Science database. We reviewed the policies related to public availability of papers and data sharing in the 85 journals included in the ISLS category of the Journal Citation Reports in 2012. The relationship between public availability of published data and impact factor of journals is analysed through different statistical tests. The variable statement of complementary material was accepted in 50 % of the journals; 65 % of the journals support reuse; 67 % of the journals specified in thematic or institutional repositories; the of the manuscript in a website was accepted in 69 % of the journals. We have found a 50 % of journals that include the possibility to deposit data as supplementary material, and more than 60 % accept reuse, storage in repositories and publication in websites. There is a clear positive relationship between being a top journal in impact factor ranking of JCR and having an open policy.

Proposal of using scaling for calculating field-normalized citation scores

Since the end of the 1980s, citation impact values –especially for evaluative purposes– are increasingly presented as field-normalized citation scores than as bare citation counts or citation rates. In rather popular variants of the scores, the average score over a publication year is not exactly one due to multiple Web of Science subject categories per paper. We propose a scaling method which introduces slight changes in the field-normalized scores of each paper that ensures that the average value of all scores equals one.