Journal articles: 'Normalized citation'

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Dechow, Patricia M., Richard G. Sloan, and Jean (Jieyin) Zeng. "Is It a Home Run? Measuring Relative Citation Rates in Accounting Research." Accounting Horizons 34, no. 1 (2019): 67–91. http://dx.doi.org/10.2308/acch-52570.

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SYNOPSIS We propose a new set of citation metrics for evaluating the relative impact of scholarly research in accounting. Our metrics are based on current practices in bibliometrics and normalize citations by both field (accounting) and year of publication. We show that our normalized citation metrics dominate other commonly used metrics in accounting when predicting the long-term citation impact of recently published research. We conduct our analysis using citations from the Social Science Citation Index for the top six general interest accounting journals. More generally, our metrics can be readily constructed using any citation database and for any subfield of accounting. The metrics simply require the total citation counts for a benchmark set of papers published in the same calendar year. The use of these metrics should enable more informed performance evaluations of junior accounting researchers.

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Dengler, Jürgen. "Determinants of citation impact." Vegetation Classification and Survey 5 (August 23, 2024): 169–77. http://dx.doi.org/10.3897/vcs.126956.

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This article aims to quantitatively assess how different formal aspects – beyond the relevance and quality of a study – influence how often a scientific paper is cited. As a case study, I retrieved all publications co-authored by myself from the Scopus database, of which 174 could be used for regression modelling. The citation impact was quantified as Field-Weighted Citation Impact (FWCI), which is the citation number normalised by year, subject area and article type. I examined 13 easily accessible numeric and binary predictor variables, including the Source Normalized Impact per Paper (SNIP), open access, special feature, number of authors, length of article and title, as well as formal aspects of the title. In the minimal adequate model, these formal aspects explained 50.2% of the variance in FWCI, with the SNIP alone explaining only 26.8%. Other strong positive predictors were title brevity, article length, special feature and the use of a colon in the title. By contrast, open access and the formulation of titles as factual statements did not have a significant effect. For authors who wish to make their articles more impactful, the main recommendation is to shorten the title and to disregard using factual statements that make the title longer. Abbreviations: FWCI = Field-weighted Citation Impact; JIF = Journal Impact Factor; OA = open access; SNIP = Source Normalized Impact per Paper: VCS = Vegetation Classification and Survey.

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Dengler, Jürgen. "Determinants of citation impact." Vegetation Classification and Survey 5 (August 23, 2024): 169–77. https://doi.org/10.3897/VCS.126956.

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This article aims to quantitatively assess how different formal aspects – beyond the relevance and quality of a study – influence how often a scientific paper is cited. As a case study, I retrieved all publications co-authored by myself from the Scopus database, of which 174 could be used for regression modelling. The citation impact was quantified as Field-Weighted Citation Impact (FWCI), which is the citation number normalised by year, subject area and article type. I examined 13 easily accessible numeric and binary predictor variables, including the Source Normalized Impact per Paper (SNIP), open access, special feature, number of authors, length of article and title, as well as formal aspects of the title. In the minimal adequate model, these formal aspects explained 50.2% of the variance in FWCI, with the SNIP alone explaining only 26.8%. Other strong positive predictors were title brevity, article length, special feature and the use of a colon in the title. By contrast, open access and the formulation of titles as factual statements did not have a significant effect. For authors who wish to make their articles more impactful, the main recommendation is to shorten the title and to disregard using factual statements that make the title longer. Abbreviations: FWCI = Field-weighted Citation Impact; JIF = Journal Impact Factor; OA = open access; SNIP = Source Normalized Impact per Paper: VCS = Vegetation Classification and Survey.

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García Martínez, Ana Teresa, Vicente P. Guerrero-Bote, and Felix De Moya-Anegón. "Scientific Production in Psychology." Universitas Psychologica 11, no. 3 (2012): 718. http://dx.doi.org/10.11144/javeriana.upsy11-3.wspp.

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This study examines world scientific production in Psychology based on bibliometric indicators (scientific production, production’s percentage variation, average citations per document, normalized citation, impact, etc.), for the period 2003–2008. The analysis is made by country, by research institutions, and scientific journals, using the Scopus (Elsevier), database of scientific literature. The results show that total world production has increased over the period studied. Four groups are acknowledge for each country, institutions, and journals, taking into account their values of scientific production, normalized citation, and subject specialization.

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Bornmann, Lutz. "How can citation impact in bibliometrics be normalized? A new approach combining citing-side normalization and citation percentiles." Quantitative Science Studies 1, no. 4 (2020): 1553–69. http://dx.doi.org/10.1162/qss_a_00089.

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Since the 1980s, many different methods have been proposed to field-normalize citations. In this study, an approach is introduced that combines two previously introduced methods: citing-side normalization and citation percentiles. The advantage of combining two methods is that their advantages can be integrated in one solution. Based on citing-side normalization, each citation is field weighted and, therefore, contextualized in its field. The most important advantage of citing-side normalization is that it is not necessary to work with a specific field categorization scheme for the normalization procedure. The disadvantages of citing-side normalization—the calculation is complex and the numbers are elusive—can be compensated for by calculating percentiles based on weighted citations that result from citing-side normalization. On the one hand, percentiles are easy to understand: They are the percentage of papers published in the same year with a lower citation impact. On the other hand, weighted citation distributions are skewed distributions with outliers. Percentiles are well suited to assigning the position of a focal paper in such distributions of comparable papers. The new approach of calculating percentiles based on weighted citations is demonstrated in this study on the basis of a citation impact comparison between several countries.

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Kochetkov, Dmitry. "A Correlation Analysis of Normalized Indicators of Citation." Publications 6, no. 3 (2018): 39. http://dx.doi.org/10.3390/publications6030039.

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Recently, more and more countries are entering the global race for university competitiveness. On the one hand, global rankings are a convenient tool for quantitative analysis. On the other hand, their indicators are often difficult to quickly calculate and they often contradict each other. The author of this paper hoped to use widely available indicators for a quick analysis of the University’s publication strategy and opted for the normalized citation indicators available in the SciVal analytical tool, namely, Source Normalized Impact per Paper (SNIP) and Field-Weighted Citation Impact (FWCI). The author demonstrated the possibility of applying the correlation analysis to the impact indicators of a document and a journal on a sample of social and humanitarian fields at Peoples’ Friendship University of Russia (PFUR, “RUDN” in Russian). A dot diagram of university (or country) documents was used to form a two-factor matrix (SNIP and FWCI) that was further divided into four quadrants. Such an analysis illustrated the present situation in that discipline. An analysis of the RUDN university publications revealed problems and prospects in the development of social sciences and humanities. A serious problem observed was that high-quality results were often published in low-impact journals that narrowed the results’ potential audience and, accordingly, the number of citations. A particular attention was paid to the application of the results in practice.

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Redman, Arnold L., Herman Manakyan, and John R. Tanner. "A Normalized Citation Analysis of Real Estate Journals." Real Estate Economics 27, no. 1 (1999): 169–82. http://dx.doi.org/10.1111/1540-6229.00770.

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Holsapple, Clyde W., Linda Ellis Johnson, Herman Manakyan, and John Tanner. "Business Computing Research Journals: A Normalized Citation Analysis." Journal of Management Information Systems 11, no. 1 (1994): 131–40. http://dx.doi.org/10.1080/07421222.1994.11518033.

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González-Betancor, Sara M., and Pablo Dorta-González. "An indicator of the impact of journals based on the percentage of their highly cited publications." Online Information Review 41, no. 3 (2017): 398–411. http://dx.doi.org/10.1108/oir-01-2016-0008.

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Purpose The two most used citation impact indicators in the assessment of scientific journals are, nowadays, the impact factor and the h-index. However, both indicators are not field normalized (vary heavily depending on the scientific category). Furthermore, the impact factor is not robust to the presence of articles with a large number of citations, while the h-index depends on the journal size. These limitations are very important when comparing journals of different sizes and categories. The purpose of this paper is to propose an alternative citation impact indicator, based on the percentage of highly cited articles in the journal. Design/methodology/approach This alternative indicator is empirically compared with the impact factor and the h-index, considering different time windows and citation percentiles (levels of citation for considering an article as highly cited compared to others in the same year and category). The authors use four journal categories (Clarivate Analytics Web of Science) which are quite different according to the publication profiles and citation levels (Information Science & Library Science, Operations Research & Management Science, Ophthalmology, and Physics Condensed Matter). Findings After analyzing 20 different indicators, depending on the citation percentile and the time window in which citations are counted, the indicator that seems to best homogenize the categories is the one that considers a time window of two years and a citation level of 10 percent. Originality/value The percentage of highly cited articles in a journal is field normalized (comparable between scientific categories), independent of the journal size and also robust to the presence of articles with a high number of citations.

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Znamenskaya, Ekaterina, Andrey Pechnikov, and Dmitry Chebukov. "Analysis of the Russian Scientific Citation Index according to Math-Net.ru Data." Russian Digital Libraries Journal 26, no. 6 (2024): 778–95. https://doi.org/10.26907/1562-5419-2023-26-6-778-795.

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Starting from spring 2022 a national system for evaluating the effectiveness of scientific research and development is being created using the database of leading Russian journals Russian Science Citation Index (RSCI). The article represents some results of the analysis of the RSCI normalized rating published in December 2022. Using the journal citation graph constructed from the data Math-Net.Ru on the example of thematic group OECD 101.Mathematics we show that in the case of a large number of self-citations of the journals, a relationship between the normalized rating and the number of references is found, and the relationship with self-citation is somewhat stronger than without self-citation. Analysis of the distribution of the journals by thematic groups shows that using a single attribute, such as the OECD, as a criterion does not allow forming a group as a community of journals with a single strongly connected component in the citation graph. We conclude that the research methods of journal citation graphs are a good basis for a comparative analysis of the characteristics of journals and their ranking, which means they can be used as tools for further development and improvement of journal ratings.

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Bornmann, Lutz, and Robin Haunschild. "Citation score normalized by cited references (CSNCR): The introduction of a new citation impact indicator." Journal of Informetrics 10, no. 3 (2016): 875–87. http://dx.doi.org/10.1016/j.joi.2016.07.002.

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Haunschild, Robin, and Lutz Bornmann. "Proposal of using scaling for calculating field-normalized citation scores." El Profesional de la Información 25, no. 1 (2016): 11. http://dx.doi.org/10.3145/epi.2016.ene.02.

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Kumar, Vikas, and Ik‐Whan G. Kwon. "A pilot study on normalized weighted approach to citation study." International Journal of Physical Distribution & Logistics Management 34, no. 10 (2004): 811–26. http://dx.doi.org/10.1108/09600030410571374.

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M., Bharathi, and Aditya Sai Srinivas T. "Beyond the H-Index: Unlocking Insights with Diverse Citation Tools." Journal of Applied Mathematics and Statistical Analysis 5, no. 2 (2024): 1–10. https://doi.org/10.5281/zenodo.10984407.

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Scholarly impact assessment relies heavily on citation analysis, with various platforms offering distinct methodologies and metrics. This abstract provides a concise overview of prominent citation analysis tools, including Dimensions, Google Scholar, Scimagojr, Scinapse, and Scopus. Each platform offers unique features and metrics, such as citation counts, h-indexes, and field-normalized impact measures, catering to diverse research needs. Researchers navigate these platforms to assess academic influence, track citation trends, and identify collaboration opportunities. Understanding the strengths and limitations of each tool is essential for effectively evaluating scholarly impact and fostering research excellence in the digital age.

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Rodriguez-Esteban, Raul. "Semantic persistence of ambiguous biomedical names in the citation network." Bioinformatics 36, no. 7 (2019): 2224–28. http://dx.doi.org/10.1093/bioinformatics/btz923.

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Abstract Motivation Name ambiguity has long been a central problem in biomedical text mining. To tackle it, it has been usually assumed that names present only one meaning within a given text. It is not known whether this assumption applies beyond the scope of single documents. Results Using a new method that leverages large numbers of biomedical annotations and normalized citations, this study shows that ambiguous biomedical names mentioned in scientific articles tend to present the same meaning in articles that cite them or that they cite, and, to a lesser extent, two steps away in the citation network. Citations, therefore, can be regarded as semantic connections between articles and the citation network should be considered for tasks such as automatic name disambiguation, entity linking and biomedical database annotation. A simple experiment shows the applicability of these findings to name disambiguation. Availability and implementation The code used for this analysis is available at: https://github.com/raroes/one-sense-per-citation-network.

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Ahlgren, Per, Cristian Colliander, and Olle Persson. "Field normalized citation rates, field normalized journal impact and Norwegian weights for allocation of university research funds." Scientometrics 92, no. 3 (2012): 767–80. http://dx.doi.org/10.1007/s11192-012-0632-x.

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M., Bharathi, and Aditya Sai Srinivas T. "Metrics Melange: Crafting a Holistic View of Journal Impact." Recent Innovations in Wireless Network Security 6, no. 3 (2024): 1–7. https://doi.org/10.5281/zenodo.10846766.

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In the realm of scientific publishing, the pursuit of an effective metric for assessing journal impact persists. The Journal Citation Indicator (JCI), introduced by Clarivate Analytics, aims to provide a field-normalized, easily comparable measure of a journal's influence. Calculated based on the Category Normalized Citation Impact (CNCI) at the article level, JCI offers a comprehensive evaluation by considering specific characteristics of different fields and their publications. While acknowledging the prominence of citation-based metrics, this abstract advocates for a broader perspective, incorporating measures such as downloads and Altmetric scores. It emphasizes the need for a holistic assessment, recognizing the multidimensional nature of journal impact, and the importance of community engagement. Ultimately, JCI serves as a valuable tool, complementing existing metrics and fostering a deeper understanding of journal significance.

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Bihari, Anand, Sudhakar Tripathi, and Akshay Deepak. "Collaboration Network Analysis Based on Normalized Citation Count and Eigenvector Centrality." International Journal of Rough Sets and Data Analysis 6, no. 1 (2019): 61–72. http://dx.doi.org/10.4018/ijrsda.2019010104.

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In the research community, the estimation of the scholarly impact of an individual is based on either citation-based indicators or network centrality measures. The network-based centrality measures like degree, closeness, betweenness & eigenvector centrality and the citation-based indicators such as h-index, g-index & i10-index, etc., are used and all of the indicators give full credit to all of the authors of a particular article. This is although the contribution of the authors are different. To determine the actual contribution of an author in a particular article, we have applied arithmetic, geometric and harmonic counting methods for finding the actual contribution of an individual. To find the prominent actor in the network, we have applied eigenvector centrality. To authenticate the proposed analysis, an experimental study has been conducted on 186007 authors collaboration network, that is extracted from IEEE Xplore. The experimental results show that the geometric counting-based credit distribution among scholars gives better results than others.

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Bornmann, Lutz, Adam Ye, and Fred Ye. "Identifying landmark publications in the long run using field-normalized citation data." Journal of Documentation 74, no. 2 (2018): 278–88. http://dx.doi.org/10.1108/jd-07-2017-0108.

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Purpose The purpose of this paper is to propose an approach for identifying landmark papers in the long run. These publications reach a very high level of citation impact and are able to remain on this level across many citing years. In recent years, several studies have been published which deal with the citation history of publications and try to identify landmark publications. Design/methodology/approach In contrast to other studies published hitherto, this study is based on a broad data set with papers published between 1980 and 1990 for identifying the landmark papers. The authors analyzed the citation histories of about five million papers across 25 years. Findings The results of this study reveal that 1,013 papers (less than 0.02 percent) are “outstandingly cited” in the long run. The cluster analyses of the papers show that they received the high impact level very soon after publication and remained on this level over decades. Only a slight impact decline is visible over the years. Originality/value For practical reasons, approaches for identifying landmark papers should be as simple as possible. The approach proposed in this study is based on standard methods in bibliometrics.

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Badenhorst, Cecile, Abu Arif, and Kelvin Quintyne. "Doctoral writing and the politics of citation use." Discourse and Writing/Rédactologie 32 (July 4, 2022): 262–80. http://dx.doi.org/10.31468/dwr.969.

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Conventions shape scholarly writing and citations practices are one set of conventions that dominate how and what we write. Yet, many of these practices naturalize exclusion and discrimination in a way that becomes normalized and, consequently, invisible. For doctoral students, learning the conventions of citing is part of developing an identity around scholarship, research and writing. In this paper, we examine our own experiences of the politics of citations to understand our socialization processes and resistances. We use an autoethnographic narrative approach to frame this qualitative study. Our findings show how citation use abounds with the contradictions and paradoxes in our doctoral writing journeys where the pressure to succeed can compromise identity-building as ethical scholars. Each of us has many needs and multiple positionalities and resisting the naturalizing grammar of citations can be complicated. Yet, once aware of the politics of citations, one cannot go back to being unaware.

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Lis, Andrzej, and Mateusz Tomanek. "Mapping the intellectual and conceptual structure of physical education research: Direct citation analysis." Physical education of students 25, no. 2 (2021): 67–84. http://dx.doi.org/10.15561/20755279.2021.0201.

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Background and Study Aim. The aim of the study is to identify and explore the intellectual and conceptual structure of physical education research. It is focused around the following study questions: (1) What are the most influential publications within the research field? (2) What are the research fronts in physical education studies? Material and Methods. As a result of the research sampling process, the 10,334 publications indexed in the Scopus database were selected by the title search for the phrase ‘physical education’. Citation analysis, one of science mapping methods, was employed to conduct the analysis. The study process and the visualization of its findings were supported by the VOSviewer software. In the process of citation analysis, we used the following weight attributes: (1) custom weight attributes: the number of citations received by a document and the normalized of citations for a document, and (2) standard weight attributes: the number of citation links. Results. Firstly, the most prominent references have been pointed out and discussed. The study of the effects of the SPARK physical education program in regard to physical activity of elementary school pupils by Sallis et al. (1997) is found to be the most cited publication in the physical education research field. The systematic literature review and meta-analysis of research on application of self-determination theory in the physical education context by Vasconellos et al. (2020) is recognized as the publication of the highest value of the normalized number of citations. The application of self-determination theory of motivation in physical education is the topic attracting a lot of attention of the top cited publications in the field. The prominent and central position of these references is confirmed by the analysis of citation links. Secondly, the following research fronts in physical education studies have been identified: (1) motivation in physical education, (2) physical education programmes, (3) development of physical education, (4) self-determination in physical education, (5) physical education and students’ academic achievement, (6) support of physical activity autonomy, (7) gender and physical education, and (8) long-term effects of physical education. Combining the research fronts identified with co-word analysis and direct citation analysis, the two-dimensional matrix mapping the conceptual structure of the physical education research field has been developed. The matrix categorizes publications according to their themes and the age of students / the levels of education, which are the object of the analysed studies. Conclusions. The study contributes mainly to development of theory through mapping the scientific output within the physical education research field. Identification of core references provides valuable information for the scholars cultivating the field about the most recognized classical works receiving the highest number of citations and ‘emerging stars’ of the highest normalized number of citations. Such information is crucial for any theoretical reviews regarding the issues of physical education. Discovering research fronts points out the themes of the highest prominence and may be an indication for searching prospective research topics by authors. Developing the matrix to be used for mapping the conceptual structure of the research field is another contribution of the study.

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Kuchanskyi, Oleksandr, Yurii Andrashko, Andrii Biloshchytskyi, et al. "Gender-Related Differences in the Citation Impact of Scientific Publications and Improving the Authors’ Productivity." Publications 11, no. 3 (2023): 37. http://dx.doi.org/10.3390/publications11030037.

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The article’s purpose is an analysis of the citation impact of scientific publications by authors of different gender compositions. The page method was chosen to calculate the citation impact of scientific publications, and the obtained results allowed to estimate the impact of the scientific publications based on the number of citations. The normalized citation impact is calculated according to nine subsets of scientific publications that correspond to patterns of different gender compositions of authors. Also, these estimates were calculated for each country with which the authors of the publications are affiliated. The Citation database, Network Dataset (Ver. 13), was chosen for the scientometric analysis. The dataset includes more than 5 million scientific publications and 48 million citations. Most of the publications in the dataset are from the STEM field. The results indicate that articles with a predominantly male composition are cited more than articles with a mixed or female composition of authors in this direction. Analysis of advantages in dynamics indicates that in the last decade, in developed countries, there has been a decrease in the connection between the citation impact of scientific publications and the gender composition of their authors. However, the obtained results still confirm the presence of gender inequality in science, which may be related to socioeconomic and cultural characteristics, natural homophily, and other factors that contribute to the appearance of gender gaps. An essential consequence of overcoming these gaps, including in science, is ensuring the rights of people in all their diversity.

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Tarazona, Beatriz, Rut Lucas-Dominguez, Vanessa Paredes-Gallardo, Adolfo Alonso-Arroyo, and Antonio Vidal-Infer. "The 100 most-cited articles in orthodontics: A bibliometric study." Angle Orthodontist 88, no. 6 (2018): 785–96. http://dx.doi.org/10.2319/012418-65.1.

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ABSTRACT Objectives: To identify and analyze the 100 most-cited articles in orthodontics indexed in the Web of Science Category of “Dental, Oral Surgery and Medicine” from 1946 to 2016. Materials and Methods: On hundred articles were identified in a search of the database of the ISI Web of Science and Journal Citation Reports, applying the truncated search term “orthodon*.” Records were manually refined and normalized to unify terms and to remove typographical, transcription, and/or indexing errors. Results: The 100 most-cited articles were published between 1946 and 2012, with numbers of citations ranging from 115 to 881. Of the 251 authors participating, 87.65% published a single work, while three authors published four works. Most of the authors with several citations were from the United States, although the University of Oslo produced the highest number of frequently cited works. Most of the articles were clinical studies, and the most frequently cited topic was mini-implants. It was noted that self-citation could be a potential cause of bias in bibliometric analysis. Conclusions: This bibliometric citation analysis reveals new, useful, and interesting information about scientific progress in the field of orthodontics.

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Bornmann, Lutz, and Loet Leydesdorff. "Count highly-cited papers instead of papers with h citations: use normalized citation counts and compare “like with like”!" Scientometrics 115, no. 2 (2018): 1119–23. http://dx.doi.org/10.1007/s11192-018-2682-1.

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Ruiz-Castillo, Javier, and Ludo Waltman. "Field-normalized citation impact indicators using algorithmically constructed classification systems of science." Journal of Informetrics 9, no. 1 (2015): 102–17. http://dx.doi.org/10.1016/j.joi.2014.11.010.

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Okamura, Keisuke. "Scientometric engineering: Exploring citation dynamics via arXiv eprints." Quantitative Science Studies 3, no. 1 (2022): 122–46. http://dx.doi.org/10.1162/qss_a_00174.

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Abstract Scholarly communications have been rapidly integrated into digitized and networked open ecosystems, where preprint servers have played a pivotal role in accelerating the knowledge transfer processes. However, quantitative evidence is scarce regarding how this paradigm shift beyond the traditional journal publication system has affected the dynamics of collective attention on science. To address this issue, we investigate the citation data of more than 1.5 million eprints on arXiv (https://arxiv.org) and analyze the long-term citation trend for each discipline involved. We find that the typical growth and obsolescence patterns vary across disciplines, reflecting different publication and communication practices. The results provide unique evidence of the attention dynamics shaped by the research community today, including the dramatic growth and fast obsolescence of Computer Science eprints, which has not been captured in previous studies relying on the citation data of journal papers. Subsequently, we develop a quantitatively and temporally normalized citation index with an approximately normal distribution, which is useful for comparing citational attention across disciplines and time periods. Further, we derive a stochastic model consistent with the observed quantitative and temporal characteristics of citation growth and obsolescence. The findings and the developed framework open a new avenue for understanding the nature of citation dynamics.

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Tomar, Manish, Sunil Prajapat, Dheeraj Kumar, Pankaj Kumar, Rajesh Kumar, and Athanasios V. Vasilakos. "Exploring the Role of Material Science in Advancing Quantum Machine Learning: A Scientometric Study." Mathematics 13, no. 6 (2025): 958. https://doi.org/10.3390/math13060958.

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Quantum Machine Learning (QML) opens up exciting possibilities for tackling problems that are incredibly complex and consume a lot of time. The drive to make QML a reality has sparked significant progress in material science, inspiring a growing number of research publications in the field. In this study, we extracted articles from the Scopus database to understand the contribution of material science in the advancement of QML. This scientometric analysis accumulated 1926 extracted publications published over 11 years spanning from 2014 to 2024. A total of 55 countries contributed to this domain of QML, among which the top 10 countries contributed 65.7% out of the total number of publications; the USA is on top, with 19.47% of the publications globally. A total of 57 authors contributed to this research area from 55 different countries. From 2014 to 2024, publications had an average citation impact of 32.12 citations per paper; the year 2015 received 16.7% of the total citations, which is the highest in the 11 years, and the year 2014 had the highest number of citations per paper, which is 61.4% of the total. The study also identifies the most significant document in the year 2017, with the source title Journal of Physics Condensed Matter, having a citation count of 2649 and a normalized citation impact index (NCII) of 91.34.

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Daniel, Torres-Salinas, Robinson-García Nicolás, Herrera-Viedma Enrique, and Jiménez-Contreras Evaristo. "Consideraciones metodológicas sobre uso del impacto normalizado en convocatorias severo ochoa y maría de maeztu." El profesional de la información 27, no. 2 (2018): 367–74. https://doi.org/10.3145/epi.2018.mar.15.

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Methodological considerations on the use of the normalized impact in the Severo Ochoa and María de Maeztu programmes Resumen En 2011 se lanzaron por primera vez las convocatorias Apoyo y acreditación de Centros de Excelencia Severo Ochoa y a Unidades de Excelencia María de Maeztu. Desde entonces estas acreditaciones se han convertido en uno de los ejes de la política científica española, distribuyéndose 186 millones de € y acreditando a 26 centros y 16 unidades. A nivel bibliométrico uno de los criterios de evaluación más llamativos es la necesidad de que los investigadores garantes tengan un Impacto Normalizado de, al menos, 1,5. En este trabajo analizamos críticamente el origen, en los años ochenta, de este indicador bibliométrico normalizado, las variantes que se han propuesto y las limitaciones de su uso en esta convocatoria nacional. Finalmente se ofrece una serie de recomendaciones prácticas para un uso más adecuado y preciso del indicador de Impacto Normalizado con fines evaluativos. Palabras Clave Indicadores bibliométricos; Métodos bibliométricos; Citación normalizada; Impacto normalizado; Evaluación; Indicador Crown; Política científica; Centros de excelencia. Abstract In 2011, the research programmes for Support and accreditation of Severo Ochoa Centers of Excellence and Units of Excellence María de Maeztu were launched for the first time. Since then, these accreditations have become one of the axes of the Spanish scientific policy. In these years, € 186 million have been distributed and 26 centers and 16 units have been accredited. At the bibliometric level, one of the most relevant evaluation criteria is the need for guarantor researchers to have a Normalized Impact of, at least, 1.5. In this work, we critically analyze the origin of this bibliometric indicator in the eighties, the variants that have been proposed and the limitations of its use in this national call. Finally we offer a series of practical recommendations for a more accurate use of the Normalized Impact indicator for evaluative purposes. Keywords Bibliometric indicators; Bibliometric methods; Normalized citation; Normalized impact; Crown indicator; Research policy; Research evaluation; Assessment; Research performance; Centers of excellence.

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Thelwall, Mike, and Pardeep Sud. "Greater female first author citation advantages do not associate with reduced or reducing gender disparities in academia." Quantitative Science Studies 1, no. 3 (2020): 1283–97. http://dx.doi.org/10.1162/qss_a_00069.

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Ongoing problems attracting women into many Science, Technology, Engineering and Mathematics (STEM) subjects have many potential explanations. This article investigates whether the possible undercitation of women associates with lower proportions of, or increases in, women in a subject. It uses six million articles published in 1996–2012 across up to 331 fields in six mainly English-speaking countries: Australia, Canada, Ireland, New Zealand, the United Kingdom and the United States. The proportion of female first- and last-authored articles in each year was calculated and 4,968 regressions were run to detect first-author gender advantages in field normalized article citations. The proportion of female first authors in each field correlated highly between countries and the female first-author citation advantages derived from the regressions correlated moderately to strongly between countries, so both are relatively field specific. There was a weak tendency in the United States and New Zealand for female citation advantages to be stronger in fields with fewer women, after excluding small fields, but there was no other association evidence. There was no evidence of female citation advantages or disadvantages to be a cause or effect of changes in the proportions of women in a field for any country. Inappropriate uses of career-level citations are a likelier source of gender inequities.

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Thelwall, Mike, and Ruth Fairclough. "All downhill from the PhD? The typical impact trajectory of U.S. academic careers." Quantitative Science Studies 1, no. 3 (2020): 1334–48. http://dx.doi.org/10.1162/qss_a_00072.

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Within academia, mature researchers tend to be more senior, but do they also tend to write higher impact articles? This article assesses long-term publishing (16+ years) United States (U.S.) researchers, contrasting them with shorter-term publishing researchers (1, 6, or 10 years). A long-term U.S. researcher is operationalized as having a first Scopus-indexed journal article in exactly 2001 and one in 2016–2019, with U.S. main affiliations in their first and last articles. Researchers publishing in large teams (11+ authors) were excluded. The average field and year normalized citation impact of long- and shorter-term U.S. researchers’ journal articles decreases over time relative to the national average, with especially large falls for the last articles published, which may be at least partly due to a decline in self-citations. In many cases researchers start by publishing above U.S. average citation impact research and end by publishing below U.S. average citation impact research. Thus, research managers should not assume that senior researchers will usually write the highest impact papers.

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Dorta-González, Pablo, María Isabel Dorta-González, Dolores Rosa Santos-Peñate, and Rafael Suárez-Vega. "Journal topic citation potential and between-field comparisons: The topic normalized impact factor." Journal of Informetrics 8, no. 2 (2014): 406–18. http://dx.doi.org/10.1016/j.joi.2014.01.013.

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Waltman, Ludo, and Nees Jan van Eck. "Field-normalized citation impact indicators and the choice of an appropriate counting method." Journal of Informetrics 9, no. 4 (2015): 872–94. http://dx.doi.org/10.1016/j.joi.2015.08.001.

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Carley, Stephen, Alan L. Porter, Ismael Rafols, and Loet Leydesdorff. "Visualization of Disciplinary Profiles: Enhanced Science Overlay Maps." Journal of Data and Information Science 2, no. 3 (2017): 68–111. http://dx.doi.org/10.1515/jdis-2017-0015.

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Abstract Purpose The purpose of this study is to modernize previous work on science overlay maps by updating the underlying citation matrix, generating new clusters of scientific disciplines, enhancing visualizations, and providing more accessible means for analysts to generate their own maps. Design/methodology/approach We use the combined set of 2015 Journal Citation Reports for the Science Citation Index (n of journals = 8,778) and the Social Sciences Citation Index (n = 3,212) for a total of 11,365 journals. The set of Web of Science Categories in the Science Citation Index and the Social Sciences Citation Index increased from 224 in 2010 to 227 in 2015. Using dedicated software, a matrix of 227 × 227 cells is generated on the basis of whole-number citation counting. We normalize this matrix using the cosine function. We first develop the citing-side, cosine-normalized map using 2015 data and VOSviewer visualization with default parameter values. A routine for making overlays on the basis of the map (“wc15.exe”) is available at http://www.leydesdorff.net/wc15/index.htm. Findings Findings appear in the form of visuals throughout the manuscript. In Figures 1–9 we provide basemaps of science and science overlay maps for a number of companies, universities, and technologies. Research limitations As Web of Science Categories change and/or are updated so is the need to update the routine we provide. Also, to apply the routine we provide users need access to the Web of Science. Practical implications Visualization of science overlay maps is now more accurate and true to the 2015 Journal Citation Reports than was the case with the previous version of the routine advanced in our paper. Originality/value The routine we advance allows users to visualize science overlay maps in VOSviewer using data from more recent Journal Citation Reports.

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Győrffy, Balázs, Boglárka Weltz, Gyöngyi Munkácsy, Péter Herman, and István Szabó. "Evaluating individual scientific output normalized to publication age and academic field through the Scientometrics.org project." Methodology 18, no. 4 (2022): 278–97. http://dx.doi.org/10.5964/meth.9463.

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When evaluating the publication performance of a scientist one has to consider not only the difference in publication norms in different scientific fields, but also the length of the academic career of the investigated researcher. Here, our goal was to establish a database suitable as a reference for the ranking of scientific performance by normalizing the researchers output to those with the same academic career length and active in same scientific field. By using the complete publication and citation data of 17,072 Hungarian researchers, we established a framework enabling the quick assessment of a researcher’s scientific output by comparing four parameters (h-index, yearly independent citations received, number of publications, and number of high impact publications), to the age-matched values of all other researchers active in the same scientific discipline. The established online tool available at www.scientometrics.org could be an invaluable help for faster and more evidence-based grant review processes.

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M., Bharathi, Aditya Sai Srinivas T., and Sri K.Teja. "The Metric Frontier SNIP & SJR as Guides to Journal Quality." Research and Reviews: Advancement in Robotics 7, no. 2 (2024): 18–24. https://doi.org/10.5281/zenodo.10862739.

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This abstract explores the significance of SNIP (Source Normalized Impact per Paper) and SJR (Scimago Journal Rank) metrics in assessing academic journal impact and prestige. It elucidates their role as alternative measures to the traditional Impact Factor, providing nuanced perspectives on journal quality. SNIP normalizes citation practices across diverse fields, ensuring fair comparisons, while SJR incorporates the prestige of citing journals, offering a comprehensive evaluation. Emphasizing transparency and accessibility, these metrics enable global comparisons of journals, aiding researchers and institutions in informed decision-making. Understanding SNIP and SJR enhances the evaluation toolkit, facilitating a deeper understanding of scholarly impact and facilitating effective journal selection.

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Sanchez-Tena, Miguel Angel, Cristina Alvarez-Peregrina, Jose Sanchez-Valverde, and Cesar Villa-Collar. "Current State and Future Trends: A Citation Network Analysis of the Orthokeratology Field." Journal of Ophthalmology 2019 (March 7, 2019): 1–6. http://dx.doi.org/10.1155/2019/6964043.

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Introduction. Citation network analysis is a powerful tool that allows for a visual and objective representation of the past, present, and potential future directions of a research field. The objective of this study is using citation analysis network to analyse the evolution of knowledge in the field of orthokeratology. Materials and Methods. The database used in this citation networks analysis study was Scopus. The descriptor used was “orthokeratology” limited to three fields: title, keywords, and/or abstract, analysing the five most cited authors. Only articles cited at least twenty times were used. The computer software used was UCINET with two types of analysis, qualitative and quantitative. Results. 27 nodes have been included according to the search and inclusion criteria. In qualitative analysis, based on illustrate results, the relationships among nodes and their positions and connections show how the study of Cho et al. in 2005 is clearly positioned as a central cutoff point in the network. Quantitative analysis reveals the normalized value of the sample and shows how the study of Cho et al. in 2005 presents the highest percentage of input connections. Conclusions. This study shows the state of the flow of information in the orthokeratology field by providing links in bibliographic citations from a qualitative and quantitative point of view.

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Owlia, P., M. Vasei, B. Goliaei, and I. Nassiri. "Normalized impact factor (NIF): An adjusted method for calculating the citation rate of biomedical journals." Journal of Biomedical Informatics 44, no. 2 (2011): 216–20. http://dx.doi.org/10.1016/j.jbi.2010.11.002.

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Waltman, Ludo, and Nees Jan van Eck. "Source normalized indicators of citation impact: an overview of different approaches and an empirical comparison." Scientometrics 96, no. 3 (2012): 699–716. http://dx.doi.org/10.1007/s11192-012-0913-4.

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Bornmann, Lutz, and Robin Haunschild. "Relative Citation Ratio (RCR): An empirical attempt to study a new field-normalized bibliometric indicator." Journal of the Association for Information Science and Technology 68, no. 4 (2016): 1064–67. http://dx.doi.org/10.1002/asi.23729.

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Sangwal, Keshra. "Comparative study of scaling parameters and research output of selected highly- and moderately-cited individual authors." Journal of Computer Sciences Institute 23 (June 30, 2022): 152–64. http://dx.doi.org/10.35784/jcsi.2920.

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The real data of cumulative citations ln of selected nth paper of individual N papers published by some highly- and moderately-cited individual authors are analyzed to compare Hirsch and Hirsch-type indices h, h1, hf and hm, and citation radii R and Rf from consideration of: (1) the number An of coauthors of the paper, (2) the normalization of citations ln and cumulative fraction lnf of citation of the nth paper by mean and median citations of the citations ln of all Nc cited papers, and (3) the determination of effective rank neff of the lnf citations. Analysis of the ln(n), lnf(n) and lnf(neff) data was also carried out by using a Langmuir-type function l = l0[1-aKn/(1+Kn)], where l denotes the citations ln and lnf of all cited Nc papers arranged in the decreasing order, a is an effectiveness parameter, K is the so-called Langmuir constant, n denotes the rank n or neff of citations and l0 is the value of l when n or neff approaches zero. For a comparison of the publication output of different authors it was found that the hm index is more consistent than other indices, and it can be normalized to account for the publication career of different authors. However, Langmuir-type function is not adequate for comparison of the publication output of different authors because it describes the rank-order distribution patterns satisfactorily in terms of two parameters. To compare the publication output of different authors independent of their career length t, it is suggested to use scaling parameters h/t, hf/t and hm/t.

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Robertson, Faith C., Brian V. Nahed, Garni Barkhoudarian, et al. "2014 American Association of Neurological Surgeons/Congress of the Neurological Surgeons (AANS/CNS) Section on Tumors Guidelines: Assessing their Impact on Brain Tumor Clinical Practice." Neurosurgery 71, Supplement_1 (2025): 244. https://doi.org/10.1227/neu.0000000000003360_2014.

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INTRODUCTION: Clinical guidelines direct healthcare professionals towards evidence-based practices. Evaluating guideline impact can elucidate information penetration, relevance, effectiveness, and alignment with evolving medical knowledge and technological advancements. METHODS: Six tumor guideline categories were reviewed: low-grade glioma, newly diagnosed glioblastoma, progressive glioblastoma, metastatic brain tumors, vestibular schwannoma, and pituitary adenomas. Citation data were collected from Google Scholar and PubMed. Further online statistics, such as social media reach, and features in policy, news, and patents, were sourced from Altmetric. Online engagement was assessed through website and CNS+ mobile application visits. Data were normalized to time since publication. RESULTS: Metastatic Tumor guidelines (2019) had the highest PubMed citation rate at 26.1 per year, and webpage visits (29,100 page views 1/1/2019 - 9/30/2023. Notably, this guideline had two endorsement publications by partner societies, the Society of Neuro-Oncology (SNO) and American Society of Clinical Oncology (ASCO), concerning antiepileptic prophylaxis and steroid use, and the greatest reach on X (19.7 mentions/year). Citation rates on Google Scholar was led by Vestibular Schwannoma (2018). Non-Functioning Pituitary Adenoma led Mendeley reads. News, patent, or policy publications were led by Low-Grade Glioma at 1.5/year. CONCLUSIONS: Our study shows that the AANS/CNS Section on Tumors guidelines go beyond citations in peer-reviewed publications to include patents, online engagement, and information dissemination to the public.

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Chen, Lingmin, Mutong Yang, Nian Li, Ying He, and Yonggang Zhang. "The Correlation between Altmetric Attention Score and Traditional Bibliometrics in Top Nursing Journal Articles." Journal of Nursing Management 2023 (February 22, 2023): 1–9. http://dx.doi.org/10.1155/2023/2789960.

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Background. Altmetric Attention Score (AAS) is a quantitative measurement of the online impact of research and has a potential correlation with traditional bibliometrics. However, the correlation for nursing journal articles is still unknown. The objective of the study was to analyze the correlation between AAS and traditional bibliometrics in the top nursing journal articles. Materials and Methods. Articles published in top nursing journals (the journals with the top 20 5-year impact factors) from 2010 to 2019 were included. The correlations between AAS and citations, AAS and Relative Citation Ratio (RCR) score, AAS and Category Normalized Citation Impact (CNCI) value, and AAS and impact factors were analyzed. Statistical analyses were performed using Stata 25.0 software. Results. A total of 15,212 journal articles were included in the study. Very weak correlations were found between AASs and citations [0.124 (95% CI, 0.108–0.14)], AASs and RCRs [0.26 (95% CI, 0.244–0.275)], and AASs and CNCIs [0.207 (95% CI, 0.192–0.223)]. The weak correlations were also found between AASs and impact factors in several journals. The weak correlations between AASs and citations, AASs and CNCIs, and AASs and RCRs were also found for most journals based on subgroup analysis. Conclusions. There is very weak correlations between AASs and traditional bibliometrics in top nursing journal articles. More studies should be conducted to assess how AAS influence bibliometrics, and how they can help manage nursing journal articles and research.

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Costas, Rodrigo, Antonio Perianes-Rodríguez, and Javier Ruiz-Castillo. "On the quest for currencies of science." Aslib Journal of Information Management 69, no. 5 (2017): 557–75. http://dx.doi.org/10.1108/ajim-01-2017-0023.

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Purpose The introduction of “altmetrics” as new tools to analyze scientific impact within the reward system of science has challenged the hegemony of citations as the predominant source for measuring scientific impact. Mendeley readership has been identified as one of the most important altmetric sources, with several features that are similar to citations. The purpose of this paper is to perform an in-depth analysis of the differences and similarities between the distributions of Mendeley readership and citations across fields. Design/methodology/approach The authors analyze two issues by using in each case a common analytical framework for both metrics: the shape of the distributions of readership and citations, and the field normalization problem generated by differences in citation and readership practices across fields. In the first issue the authors use the characteristic scores and scales method, and in the second the measurement framework introduced in Crespo et al. (2013). Findings There are three main results. First, the citations and Mendeley readership distributions exhibit a strikingly similar degree of skewness in all fields. Second, the results on “exchange rates (ERs)” for Mendeley readership empirically supports the possibility of comparing readership counts across fields, as well as the field normalization of readership distributions using ERs as normalization factors. Third, field normalization using field mean readerships as normalization factors leads to comparably good results. Originality/value These findings open up challenging new questions, particularly regarding the possibility of obtaining conflicting results from field normalized citation and Mendeley readership indicators; this suggests the need for better determining the role of the two metrics in capturing scientific recognition.

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Sanfilippo, Paul, Alex W. Hewitt, and David A. Mackey. "Plurality in multi-disciplinary research: multiple institutional affiliations are associated with increased citations." PeerJ 6 (September 24, 2018): e5664. http://dx.doi.org/10.7717/peerj.5664.

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Background The institutional affiliations and associated collaborative networks that scientists foster during their research careers are salient in the production of high-quality science. The phenomenon of multiple institutional affiliations and its relationship to research output remains relatively unexplored in the literature. Methods We examined 27,612 scientific articles, modelling the normalized citation counts received against the number of authors and affiliations held. Results In agreement with previous research, we found that teamwork is an important factor in high impact papers, with average citations received increasing concordant with the number of co-authors listed. For articles with more than five co-authors, we noted an increase in average citations received when authors with more than one institutional affiliation contributed to the research. Discussion Multiple author affiliations may play a positive role in the production of high-impact science. This increased researcher mobility should be viewed by institutional boards as meritorious in the pursuit of scientific discovery.

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Kaltman, Jonathan R., Frank J. Evans, Narasimhan S. Danthi, Colin O. Wu, Donna M. DiMichele, and Michael S. Lauer. "Prior Publication Productivity, Grant Percentile Ranking, and Topic-Normalized Citation Impact of NHLBI Cardiovascular R01 Grants." Circulation Research 115, no. 7 (2014): 617–24. http://dx.doi.org/10.1161/circresaha.115.304766.

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Moed, Henk F. "The source normalized impact per paper is a valid and sophisticated indicator of journal citation impact." Journal of the American Society for Information Science and Technology 62, no. 1 (2010): 211–13. http://dx.doi.org/10.1002/asi.21424.

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Dengler, Jürgen, Idoia Biurrun, Florian Jansen, and Wolfgang Willner. "Vegetation Classification and Survey is performing well." Vegetation Classification and Survey 5 (January 19, 2024): 1–10. http://dx.doi.org/10.3897/vcs.118454.

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On the occasion of the completion of the fourth volume of Vegetation Classification and Survey (VCS), we have analysed the performance of the journal since its inception. The number of papers and pages show a moderate increase over the years. VCS has been included in the Scopus database for more than a year and received its first CiteScore of 2.0 in summer 2023 but is not yet included in the Web of Science Core Edition. We therefore used data from the Scopus database to compare the citation impact of articles in VCS with that of 29 other ecological journals. By calculating normalized citation rates per journal and publication year, we found that VCS started at the bottom of the rankings in the first two years (28th out of 30) but improved to 26th in 2022 and 14th in 2023. Together with the known time lag and the strong positive relationships between the different citation metrics, this allows a projection of the future development of the CiteScores and, after inclusion in the Web of Science, the Journal Impact Factor (JIF). Using the Field-Weighted Citation Impact (FWCI) from the Scopus database, we identified the top 12 out of 95 VCS articles published in the first four years that received more citations than expected for their age and field. We also present the four Editors’ Choice papers of 2023, among which Strohbach and Strohbach (2023; Vegetation Classification and Survey 4: 241–284) received the Editors’ Award in 2023. We conclude that VCS is on the right track, supported by the fact that in 2024 most authors will still be charged no or very low article processing charges (APCs). Abbreviations: APC = article processing charge; IAVS = International Association for Vegetation Science; JIF = Journal Impact Factor; OA = open access; VCS = Vegetation Classification and Survey; WoS = Web of Science Core Edition.

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Dengler, Jürgen, Idoia Biurrun, Florian Jansen, and Wolfgang Willner. "Vegetation Classification and Survey is performing well." Vegetation Classification and Survey 5 (January 19, 2024): 1–10. https://doi.org/10.3897/VCS.118454.

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On the occasion of the completion of the fourth volume of Vegetation Classification and Survey (VCS), we have analysed the performance of the journal since its inception. The number of papers and pages show a moderate increase over the years. VCS has been included in the Scopus database for more than a year and received its first CiteScore of 2.0 in summer 2023 but is not yet included in the Web of Science Core Edition. We therefore used data from the Scopus database to compare the citation impact of articles in VCS with that of 29 other ecological journals. By calculating normalized citation rates per journal and publication year, we found that VCS started at the bottom of the rankings in the first two years (28th out of 30) but improved to 26th in 2022 and 14th in 2023. Together with the known time lag and the strong positive relationships between the different citation metrics, this allows a projection of the future development of the CiteScores and, after inclusion in the Web of Science, the Journal Impact Factor (JIF). Using the Field-Weighted Citation Impact (FWCI) from the Scopus database, we identified the top 12 out of 95 VCS articles published in the first four years that received more citations than expected for their age and field. We also present the four Editors' Choice papers of 2023, among which Strohbach and Strohbach (2023; Vegetation Classification and Survey 4: 241–284) received the Editors' Award in 2023. We conclude that VCS is on the right track, supported by the fact that in 2024 most authors will still be charged no or very low article processing charges (APCs). Abbreviations: APC = article processing charge; IAVS = International Association for Vegetation Science; JIF = Journal Impact Factor; OA = open access; VCS = Vegetation Classification and Survey; WoS = Web of Science Core Edition.

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Bornmann, Lutz. "Bibliometrics-based decision trees (BBDTs) based on bibliometrics-based heuristics (BBHs): Visualized guidelines for the use of bibliometrics in research evaluation." Quantitative Science Studies 1, no. 1 (2020): 171–82. http://dx.doi.org/10.1162/qss_a_00012.

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Fast-and-frugal heuristics are simple strategies that base decisions on only a few predictor variables. In so doing, heuristics may not only reduce complexity but also boost the accuracy of decisions, their speed, and transparency. In this paper, bibliometrics-based decision trees (BBDTs) are introduced for research evaluation purposes. BBDTs visualize bibliometrics-based heuristics (BBHs), which are judgment strategies solely using publication and citation data. The BBDT exemplar presented in this paper can be used as guidance to find an answer on the question in which situations simple indicators such as mean citation rates are reasonable and in which situations more elaborated indicators (i.e., [sub-]field-normalized indicators) should be applied.

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Gómez-Núñez, Antonio J., Benjamin Vargas-Quesada, Zaida Chinchilla-Rodríguez, Vladimir Batagelj, and Félix Moya-Anegón. "Visualization and analysis of SCImago Journal & Country Rank structure via journal clustering." Aslib Journal of Information Management 68, no. 5 (2016): 607–27. http://dx.doi.org/10.1108/ajim-12-2015-0205.

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Purpose The purpose of this paper is to visualize the structure of SCImago Journal & Country Rank (SJR) coverage of the extensive citation network of Scopus journals, examining this bibliometric portal through an alternative approach, applying clustering and visualization techniques to a combination of citation-based links. Design/methodology/approach Three SJR journal-journal networks containing direct citation, co-citation and bibliographic coupling links are built. The three networks were then combined into a new one by summing up their values, which were later normalized through geo-normalization measure. Finally, the VOS clustering algorithm was executed and the journal clusters obtained were labeled using original SJR category tags and significant words from journal titles. Findings The resultant scientogram displays the SJR structure through a set of communities equivalent to SJR categories that represent the subject contents of the journals they cover. A higher level of aggregation by areas provides a broad view of the SJR structure, facilitating its analysis and visualization at the same time. Originality/value This is the first study using Persson’s combination of most popular citation-based links (direct citation, co-citation and bibliographic coupling) in order to develop a scientogram based on Scopus journals from SJR. The integration of the three measures along with performance of the VOS community detection algorithm gave a balanced set of clusters. The resulting scientogram is useful for assessing and validating previous classifications as well as for information retrieval and domain analysis.

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Journal articles on the topic 'Normalized citation'

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