This document discusses impact factors, which provide the average number of citations to articles in a particular journal. Impact factors are calculated based on the total citations in a given year to articles published in the two previous years, divided by the total number of articles published in those two years. There is significant variation in impact factors between different academic fields due to differences in average citations levels, publication and citation behaviors, and coverage by the database calculating the impact factors.
Impact Factor: the Journal Competition, Scientific Excellence or Fool’s Game ...crimsonpublisherscojrr
This document discusses the impact factor (IF), a metric used to evaluate journals. It was originally intended to identify high quality research, but is now often used to assess individual researchers and influence hiring/funding decisions. However, the IF has been criticized as it can be manipulated by editors and does not accurately measure any individual researcher's work. While still widely used due to its commercial value, many scientific organizations have rejected its use in research evaluation and alternative metrics are being explored, though none have replaced the IF yet. The origins and evolution of bibliometrics and the challenges around developing new qualitative measures are also examined.
Rankometrics / Bibliometrics - Les OxleyCharlies1000
This document discusses various metrics and rankings used to evaluate academic journals, known as "rankometrics". It defines several common metrics including two-year impact factor (2YIF), Eigenfactor score, h-index, and immediacy. It also introduces some new proposed metrics such as the Impact Factor Inflation score, Self-citation Threshold Approval Rating, and PI-BETA score. Economic journals are analyzed as an example, finding the 2YIF ranges from 1.369 to 5.048, journal h-indices range from 10 to 149, and PI-BETA scores indicating the percentage of uncited articles range from 0.055 to 0.856. In summary, the document outlines many existing and proposed
The presentation discusses about a Thesis, Research paper, Review Article & Technical Reports: Organization of thesis and reports, formatting issues, citation methods, references, effective oral presentation of research. Quality indices of research publication: impact factor, immediacy factor, H- index and other citation indices. A verbal consent of Prof. Dr. C. B. Bhatt was obtained (at 4.15pm on Dt. 26-11-2016 at Hall A-2, GTU, Chandkheda) to float the presentation online in benefits of the research scholar society.
Impact Factor: An Index of Research JournalAJAY SEMALTY
PLEASE SUBSCRIBE OUR YOUTUBE CHANNEL OPENKNOWLEDGE or see URL https://youtu.be/nPLnJqLEknY
Research Indices are the indicators of the credibility and recognition of a researcher, a journal, an article and/or and institute. These include Impact Factor, immediacy Index, h-index etc. Researchers and students must know about these indices for better recognition in the academia and research. In the first part of the series we are discussing Impact Factor as a vital research Index. Impact factor (IF) is the most Important basis of selection of journal by the researchers and readers. Its a a measure of the reputation of a journal. IF is a measure of the frequency with which the "average article" in a journal has been cited in a particular year. The OER shall cover how (IF is calculated), Who (provides the IF), on which factors IF depends upon, The importance of IF in academic recognition and knowing the IF of journal. Also SUBSCRIBE OUR YOUTUBE CHANNEL OPENKNOWLEDGE or see https://youtu.be/nPLnJqLEknY
Journal Impact Factors and Citation Analysisrepayne
This document discusses various metrics for measuring the impact and importance of academic journals, articles, and authors. It describes journal impact factors, citation analysis tools like Web of Knowledge and Google Scholar, metrics for individual researchers like the h-index, and newer altmetric tools that analyze social media mentions. Limitations of different metrics are also outlined.
The document discusses various quality indices used to evaluate research publications and authors. It defines indices such as the impact factor, immediacy index, Eigenfactor, SCImago Journal Rank, H-index, G-index, and HB-index. It provides details on how each index is calculated and its significance. It also discusses limitations of impact factor and compares different journal quality indices. The document aims to explain these quality metrics to evaluate journals and authors.
Discipline impact factor and discipline susceptibility factor: some of the hi...bntulibrary
The document discusses the history and definitions of discipline impact factor (DIF). DIF measures the average number of times a paper in a journal is cited by other journals in the same discipline, unlike the typical impact factor which measures citations across all sciences. While DIF was useful for selecting relevant journals for specific disciplines, it was not widely used due to the complex calculations required. Some examples of studies using DIF are provided. The concept of DIF may still be relevant for deciding which journal databases to purchase to support specific disciplines.
Impact Factor: the Journal Competition, Scientific Excellence or Fool’s Game ...crimsonpublisherscojrr
This document discusses the impact factor (IF), a metric used to evaluate journals. It was originally intended to identify high quality research, but is now often used to assess individual researchers and influence hiring/funding decisions. However, the IF has been criticized as it can be manipulated by editors and does not accurately measure any individual researcher's work. While still widely used due to its commercial value, many scientific organizations have rejected its use in research evaluation and alternative metrics are being explored, though none have replaced the IF yet. The origins and evolution of bibliometrics and the challenges around developing new qualitative measures are also examined.
Rankometrics / Bibliometrics - Les OxleyCharlies1000
This document discusses various metrics and rankings used to evaluate academic journals, known as "rankometrics". It defines several common metrics including two-year impact factor (2YIF), Eigenfactor score, h-index, and immediacy. It also introduces some new proposed metrics such as the Impact Factor Inflation score, Self-citation Threshold Approval Rating, and PI-BETA score. Economic journals are analyzed as an example, finding the 2YIF ranges from 1.369 to 5.048, journal h-indices range from 10 to 149, and PI-BETA scores indicating the percentage of uncited articles range from 0.055 to 0.856. In summary, the document outlines many existing and proposed
The presentation discusses about a Thesis, Research paper, Review Article & Technical Reports: Organization of thesis and reports, formatting issues, citation methods, references, effective oral presentation of research. Quality indices of research publication: impact factor, immediacy factor, H- index and other citation indices. A verbal consent of Prof. Dr. C. B. Bhatt was obtained (at 4.15pm on Dt. 26-11-2016 at Hall A-2, GTU, Chandkheda) to float the presentation online in benefits of the research scholar society.
Impact Factor: An Index of Research JournalAJAY SEMALTY
PLEASE SUBSCRIBE OUR YOUTUBE CHANNEL OPENKNOWLEDGE or see URL https://youtu.be/nPLnJqLEknY
Research Indices are the indicators of the credibility and recognition of a researcher, a journal, an article and/or and institute. These include Impact Factor, immediacy Index, h-index etc. Researchers and students must know about these indices for better recognition in the academia and research. In the first part of the series we are discussing Impact Factor as a vital research Index. Impact factor (IF) is the most Important basis of selection of journal by the researchers and readers. Its a a measure of the reputation of a journal. IF is a measure of the frequency with which the "average article" in a journal has been cited in a particular year. The OER shall cover how (IF is calculated), Who (provides the IF), on which factors IF depends upon, The importance of IF in academic recognition and knowing the IF of journal. Also SUBSCRIBE OUR YOUTUBE CHANNEL OPENKNOWLEDGE or see https://youtu.be/nPLnJqLEknY
Journal Impact Factors and Citation Analysisrepayne
This document discusses various metrics for measuring the impact and importance of academic journals, articles, and authors. It describes journal impact factors, citation analysis tools like Web of Knowledge and Google Scholar, metrics for individual researchers like the h-index, and newer altmetric tools that analyze social media mentions. Limitations of different metrics are also outlined.
The document discusses various quality indices used to evaluate research publications and authors. It defines indices such as the impact factor, immediacy index, Eigenfactor, SCImago Journal Rank, H-index, G-index, and HB-index. It provides details on how each index is calculated and its significance. It also discusses limitations of impact factor and compares different journal quality indices. The document aims to explain these quality metrics to evaluate journals and authors.
Discipline impact factor and discipline susceptibility factor: some of the hi...bntulibrary
The document discusses the history and definitions of discipline impact factor (DIF). DIF measures the average number of times a paper in a journal is cited by other journals in the same discipline, unlike the typical impact factor which measures citations across all sciences. While DIF was useful for selecting relevant journals for specific disciplines, it was not widely used due to the complex calculations required. Some examples of studies using DIF are provided. The concept of DIF may still be relevant for deciding which journal databases to purchase to support specific disciplines.
Conducting a Literature Search & Writing Review Paper, Part 2: Finding proper...Nader Ale Ebrahim
12- Evaluate a paper quality
13- H-index and g-index
14- Publish or Perish
15- Evaluate a journal quality
16- The Institute for Scientific Information (ISI)
17- Impact Factor-Journal Ranking
18- Keeping up-to-date (Alert system)
19- How to Read a Paper
20- Mind mapping tools
21- Indexing desktop search tool
Journal ranking metrices new perspective in journal performance managementAboul Ella Hassanien
The document discusses various metrics for evaluating journals and research, including impact factor, immediacy index, and the h-index. It provides definitions and explanations of how these metrics are calculated. For example, it explains that impact factor is calculated by dividing the number of citations in the current year by the total number of articles published in the previous two years. It also discusses some limitations and criticisms of solely relying on impact factor for evaluations.
This document provides an overview of various bibliometric tools and metrics for measuring scientific output and impact. It discusses journal ranking metrics like impact factor, eigenfactor, SNIP, and SJR. It also covers article-level metrics including F1000 factors and citation analysis tools from Google Scholar, Web of Science, and Scopus. Additionally, it introduces author-level metrics such as the h-index and its variants that can be calculated using various databases and tools. Finally, the document briefly discusses altmetrics and ways to track scholarly impact on social media and the open web.
This document summarizes an academic study that explored expert conceptions of electricity security in the UK context of a low-carbon transition. The study conducted interviews with 25 energy experts from different organizations to discuss 22 issues related to electricity security. The interviews aimed to understand which aspects of security experts view as most important and the underlying concepts they use. The results showed that experts have diverse and competing views of security, and that their perspectives did not clearly align with their organization. The study highlights the need to consider multiple perspectives rather than try to define security with simple metrics.
This document discusses forecasting household consumption in the Czech Republic using data from Google Trends. It first reviews literature on using sentiment indicators and Google Trends data to predict consumption. It then describes the consumption and sentiment data from the Czech Statistical Office, as well as search data from Google Trends. Finally, it introduces the model that will be used to forecast consumption using these different data sources.
Impact Factor and the Evaluation of Scientists - a book chapter by Nicola de ...Xanat V. Meza
Disclaimer: all original texts and images belong to their rightful owners.
Chapter 6 of the Book "Bibliometrics and citation analysis" by Nicola de Bellis.
The document discusses various citation databases and metrics for evaluating publications and journals. It describes Web of Science, Scopus, and Google Scholar as the major citation databases. It provides details on the coverage, citation data included, and analytical tools available for each database. The document also explains journal citation reports, which allow comparison of journals using citation data. Key metrics for journals are defined, including impact factor, eigenfactor, and article influence score. Quartile comparisons that enable evaluation of journal rankings are also outlined.
International Journal of Humanities and Social Science Invention (IJHSSI)inventionjournals
International Journal of Humanities and Social Science Invention (IJHSSI) is an international journal intended for professionals and researchers in all fields of Humanities and Social Science. IJHSSI publishes research articles and reviews within the whole field Humanities and Social Science, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
This document presents a longitudinal case study of a machinery manufacturing organization that successfully developed both mass customization capabilities and green management capabilities over time. The study finds overlaps and path dependencies between individual mass customization capabilities and green management capabilities. Specifically, certain mass customization capabilities helped enable the development of specific green management capabilities and vice versa. These findings indicate synergies between pursuing mass customization and green management strategies that can help alleviate the difficulty of implementing both strategies simultaneously.
It’s important to remember that the impact factor only looks at an average citation and that a journal may have a few highly cited papers that greatly increase its impact factor, while other papers in that same journal may not be cited at all. Therefore, there is no direct correlation between an individual article’s citation frequency or quality and the journal impact factor.
Most of the junior research fellows, upcoming scientists may not be aware of - what is the impact factor, how it is calculated and how can we use the impact factor. Most of the people will think that impact factor is important in assessing the quality of a journal. Here one should keep in mind that impact factor of a journal is no way related to the main quality parameters like peer review, detection of plagiarism, citations of the articles published in a journal etc.. Though there are many review articles published on impact factor, again I have summarized those points just to educate our readers.
The document discusses the use of bibliometric data and citation metrics to evaluate research performance and support decision making. It notes the increasing importance of demonstrating research impact and return on investment. Thomson Reuters products like the Journal Citation Reports and Web of Science are positioned as providing objective citation and bibliometric data to help with research assessment and evaluation exercises. The document also provides examples of how this data can be used to analyze the research performance of institutions and individuals.
This document discusses various quality indices used to evaluate research publications and authors. It defines indices such as the impact factor, immediacy index, Eigenfactor, SCImago Journal Rank, H-index, G-index, and HB-index. It provides details on how each index is calculated and its purpose. For example, the impact factor measures the average number of citations to articles in a journal, while the H-index quantifies an individual author's scientific research output based on both their productivity and citation impact. The document also notes some criticisms of these indices and how they can be determined using databases like Web of Science and Scopus.
The impact factor (IF) is a metric that measures the average number of citations received in a given year by articles published in a journal over the previous two years. Impact factors are calculated annually and published in the Journal Citation Reports to indicate the relative significance and influence of journals within their fields. While impact factors help identify influential research and select publication targets, they should not be the sole consideration and have limitations due to variability in disciplines, editorial policies, and self-citations. Alternatives to the IF include the h-index and Eigenfactor, which aim to provide more robust assessments of research influence and output.
Modified CiteScore metric for reducing the effect of self-citationsTELKOMNIKA JOURNAL
Elsevier B.V. launched a scholarly metric called CiteScore (CS) on December 8, 2016. Up till
then, the journal impact factor (JIF) owned by Clarivate Analytics (Thomson Reuters) was the only trusted
metric for journal evaluation. As noted by Teixeira da Silva & Memon (2017), CS offers some observed
advantages over JIF. The potentials of CiteScore as a viable metric are still emerging. The paper briefly
introduces a variant of the CiteScore that can be used in quantifying the impact of researchers and their
institutions. The ultimate aim is to reduce the numerical effect of self-citations (SC) in academic publishing.
The reduction is designed to discourage SC but not diminishing it. The reasons for the adopted
methodology are discussed extensively. The proposed modified CiteScore metric is simple, transparent
and constructed to ensure integrity in academic publication. The result showed that the proposed modified
CiteScore is a better option than the traditional CiteScore and hence, can be applied in impact
determination, the ranking of authors and their institutions, and evaluation of scientists for a grant award.
The approach used in this paper is entirely new in two ways; first, a metric similar to journal ranking is
proposed for ranking authors and their institutions and secondly, disproportionate scores are awarded to
different sources of citations to reduce perceived dishonesty in academic publications. In conclusion, this
research is one of very few to report the effect of SC on CiteScore. Hitherto, the effect of SC has always
been on the journal impact factor (IF).
This document provides an overview of various bibliometric products and metrics that can be used to measure research impact, including journal impact factor, h-index, citation counts, and journal/article ranking tools from Journal Citation Reports, Scopus, and Google Scholar. It discusses the purpose and calculations of metrics like impact factor, eigenfactor, and source normalized impact per paper (SNIP). It also covers limitations of bibliometrics and recommends using multiple metrics and tools to evaluate research. Exercises are provided to help understand how to analyze journals, articles, and individual researchers using different bibliometric resources.
This document defines and explains several metrics used to measure the impact and quality of academic journals, including:
1. Impact factor, which measures the average number of citations to recent articles over a 2 year period.
2. 5-year impact factor, eigenfactor, article influence, SJR, and SNIP, which also measure citations but use different calculation methods.
3. Review speed and online publication time, which indicate how quickly journals process submissions and make articles available.
Journal ranking metrices new perspective in journal performance managementAboul Ella Hassanien
The document discusses various metrics for evaluating journals and research, including impact factor, immediacy index, and the h-index. It provides definitions and explanations of how these metrics are calculated. For example, it explains that impact factor is calculated by dividing the number of citations in the current year by the total number of articles published in the previous two years. It also discusses some limitations and criticisms of solely relying on impact factor for evaluation.
Conducting a Literature Search & Writing Review Paper, Part 2: Finding proper...Nader Ale Ebrahim
12- Evaluate a paper quality
13- H-index and g-index
14- Publish or Perish
15- Evaluate a journal quality
16- The Institute for Scientific Information (ISI)
17- Impact Factor-Journal Ranking
18- Keeping up-to-date (Alert system)
19- How to Read a Paper
20- Mind mapping tools
21- Indexing desktop search tool
Journal ranking metrices new perspective in journal performance managementAboul Ella Hassanien
The document discusses various metrics for evaluating journals and research, including impact factor, immediacy index, and the h-index. It provides definitions and explanations of how these metrics are calculated. For example, it explains that impact factor is calculated by dividing the number of citations in the current year by the total number of articles published in the previous two years. It also discusses some limitations and criticisms of solely relying on impact factor for evaluations.
This document provides an overview of various bibliometric tools and metrics for measuring scientific output and impact. It discusses journal ranking metrics like impact factor, eigenfactor, SNIP, and SJR. It also covers article-level metrics including F1000 factors and citation analysis tools from Google Scholar, Web of Science, and Scopus. Additionally, it introduces author-level metrics such as the h-index and its variants that can be calculated using various databases and tools. Finally, the document briefly discusses altmetrics and ways to track scholarly impact on social media and the open web.
This document summarizes an academic study that explored expert conceptions of electricity security in the UK context of a low-carbon transition. The study conducted interviews with 25 energy experts from different organizations to discuss 22 issues related to electricity security. The interviews aimed to understand which aspects of security experts view as most important and the underlying concepts they use. The results showed that experts have diverse and competing views of security, and that their perspectives did not clearly align with their organization. The study highlights the need to consider multiple perspectives rather than try to define security with simple metrics.
This document discusses forecasting household consumption in the Czech Republic using data from Google Trends. It first reviews literature on using sentiment indicators and Google Trends data to predict consumption. It then describes the consumption and sentiment data from the Czech Statistical Office, as well as search data from Google Trends. Finally, it introduces the model that will be used to forecast consumption using these different data sources.
Impact Factor and the Evaluation of Scientists - a book chapter by Nicola de ...Xanat V. Meza
Disclaimer: all original texts and images belong to their rightful owners.
Chapter 6 of the Book "Bibliometrics and citation analysis" by Nicola de Bellis.
The document discusses various citation databases and metrics for evaluating publications and journals. It describes Web of Science, Scopus, and Google Scholar as the major citation databases. It provides details on the coverage, citation data included, and analytical tools available for each database. The document also explains journal citation reports, which allow comparison of journals using citation data. Key metrics for journals are defined, including impact factor, eigenfactor, and article influence score. Quartile comparisons that enable evaluation of journal rankings are also outlined.
International Journal of Humanities and Social Science Invention (IJHSSI)inventionjournals
International Journal of Humanities and Social Science Invention (IJHSSI) is an international journal intended for professionals and researchers in all fields of Humanities and Social Science. IJHSSI publishes research articles and reviews within the whole field Humanities and Social Science, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
This document presents a longitudinal case study of a machinery manufacturing organization that successfully developed both mass customization capabilities and green management capabilities over time. The study finds overlaps and path dependencies between individual mass customization capabilities and green management capabilities. Specifically, certain mass customization capabilities helped enable the development of specific green management capabilities and vice versa. These findings indicate synergies between pursuing mass customization and green management strategies that can help alleviate the difficulty of implementing both strategies simultaneously.
It’s important to remember that the impact factor only looks at an average citation and that a journal may have a few highly cited papers that greatly increase its impact factor, while other papers in that same journal may not be cited at all. Therefore, there is no direct correlation between an individual article’s citation frequency or quality and the journal impact factor.
Most of the junior research fellows, upcoming scientists may not be aware of - what is the impact factor, how it is calculated and how can we use the impact factor. Most of the people will think that impact factor is important in assessing the quality of a journal. Here one should keep in mind that impact factor of a journal is no way related to the main quality parameters like peer review, detection of plagiarism, citations of the articles published in a journal etc.. Though there are many review articles published on impact factor, again I have summarized those points just to educate our readers.
The document discusses the use of bibliometric data and citation metrics to evaluate research performance and support decision making. It notes the increasing importance of demonstrating research impact and return on investment. Thomson Reuters products like the Journal Citation Reports and Web of Science are positioned as providing objective citation and bibliometric data to help with research assessment and evaluation exercises. The document also provides examples of how this data can be used to analyze the research performance of institutions and individuals.
This document discusses various quality indices used to evaluate research publications and authors. It defines indices such as the impact factor, immediacy index, Eigenfactor, SCImago Journal Rank, H-index, G-index, and HB-index. It provides details on how each index is calculated and its purpose. For example, the impact factor measures the average number of citations to articles in a journal, while the H-index quantifies an individual author's scientific research output based on both their productivity and citation impact. The document also notes some criticisms of these indices and how they can be determined using databases like Web of Science and Scopus.
The impact factor (IF) is a metric that measures the average number of citations received in a given year by articles published in a journal over the previous two years. Impact factors are calculated annually and published in the Journal Citation Reports to indicate the relative significance and influence of journals within their fields. While impact factors help identify influential research and select publication targets, they should not be the sole consideration and have limitations due to variability in disciplines, editorial policies, and self-citations. Alternatives to the IF include the h-index and Eigenfactor, which aim to provide more robust assessments of research influence and output.
Modified CiteScore metric for reducing the effect of self-citationsTELKOMNIKA JOURNAL
Elsevier B.V. launched a scholarly metric called CiteScore (CS) on December 8, 2016. Up till
then, the journal impact factor (JIF) owned by Clarivate Analytics (Thomson Reuters) was the only trusted
metric for journal evaluation. As noted by Teixeira da Silva & Memon (2017), CS offers some observed
advantages over JIF. The potentials of CiteScore as a viable metric are still emerging. The paper briefly
introduces a variant of the CiteScore that can be used in quantifying the impact of researchers and their
institutions. The ultimate aim is to reduce the numerical effect of self-citations (SC) in academic publishing.
The reduction is designed to discourage SC but not diminishing it. The reasons for the adopted
methodology are discussed extensively. The proposed modified CiteScore metric is simple, transparent
and constructed to ensure integrity in academic publication. The result showed that the proposed modified
CiteScore is a better option than the traditional CiteScore and hence, can be applied in impact
determination, the ranking of authors and their institutions, and evaluation of scientists for a grant award.
The approach used in this paper is entirely new in two ways; first, a metric similar to journal ranking is
proposed for ranking authors and their institutions and secondly, disproportionate scores are awarded to
different sources of citations to reduce perceived dishonesty in academic publications. In conclusion, this
research is one of very few to report the effect of SC on CiteScore. Hitherto, the effect of SC has always
been on the journal impact factor (IF).
This document provides an overview of various bibliometric products and metrics that can be used to measure research impact, including journal impact factor, h-index, citation counts, and journal/article ranking tools from Journal Citation Reports, Scopus, and Google Scholar. It discusses the purpose and calculations of metrics like impact factor, eigenfactor, and source normalized impact per paper (SNIP). It also covers limitations of bibliometrics and recommends using multiple metrics and tools to evaluate research. Exercises are provided to help understand how to analyze journals, articles, and individual researchers using different bibliometric resources.
This document defines and explains several metrics used to measure the impact and quality of academic journals, including:
1. Impact factor, which measures the average number of citations to recent articles over a 2 year period.
2. 5-year impact factor, eigenfactor, article influence, SJR, and SNIP, which also measure citations but use different calculation methods.
3. Review speed and online publication time, which indicate how quickly journals process submissions and make articles available.
Journal ranking metrices new perspective in journal performance managementAboul Ella Hassanien
The document discusses various metrics for evaluating journals and research, including impact factor, immediacy index, and the h-index. It provides definitions and explanations of how these metrics are calculated. For example, it explains that impact factor is calculated by dividing the number of citations in the current year by the total number of articles published in the previous two years. It also discusses some limitations and criticisms of solely relying on impact factor for evaluation.
This document discusses frameworks and indices for assessing sustainability. It begins by introducing common types of sustainability assessment tools, focusing on indicators and indices. It then outlines several widely-used sustainability frameworks, including the Triple Bottom Line framework and pressure-state-response model. Next, it describes the process for constructing sustainability indices, including selecting indicators, standardizing data, assigning weights, and aggregating the results. It notes that indicator selection and weighting are often inconsistent due to a lack of standardized requirements. Finally, it argues that sustainability frameworks can effectively guide indicator selection for both standalone indicators and composite indices.
This document provides an overview of traditional scholarly impact metrics like citation count and impact factor, as well as new developments in altmetrics. It begins with an introduction to why citations are counted and the sources of citation data. It then discusses common metrics for measuring the impact of individuals, journals, and institutions. These include the h-index, journal impact factor, and global university rankings. The document also notes some limitations and issues with traditional metrics and outlines new areas of development in altmetrics.
The document discusses the impact factor (IF), which is used to measure the importance of academic journals. It provides details on how the IF is calculated based on the number of citations over a certain period. While the IF has become influential in research, it also faces criticisms. The document aims to explain the IF to help young academics understand and apply it appropriately when publishing their work.
Prof. sp singh.ph d.course work.2020-21.citation index, journal impact factor...Saurashtra University
Citation index, Journal Impact Factors , H – Index and Impact Factor
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RESEARCH, PUBLICATIONS AND QUALITY ASSESSMENT
WIDE VARIATION IN THE ASSESSMENT AND QUALITY JUDGMENT
DIFFRENTIAL LEVEL OF RESEARCH OUTPUT- Reflected by number/frequency/quality of the publication
LACK OF INTEREST
DIFFERNCES IN OVER ALL OBJECTIVES
TYPES OF PUBLICATIONS
TYPES AND QUALITY OF THE JOURNALS
Journal and author impact measures Assessing your impact (h-index and beyond)Aboul Ella Hassanien
This seminar presented at faculty of Computers Monofiya university on Saturday 12 Dec. 2015. Seminar for researchers and graduate students at Egyptian universities to increase awareness of the importance of publication and scientific research and how to increase the researchers weight, its calculation, and calculation of magazines weight and how to calculate new weights that differ from the impact of the magazines and tips for students attic studies on how to increase citation of the published research papers and How to use open access publishing. In addition discuss the Issues in the field of open access including its advantages and disadvantages
This document provides guidance on selecting an appropriate journal to publish research. It discusses factors to consider like the paper's content, intended audience, and journal scope. It also covers differences between indexed and non-indexed journals, as well as open access and subscription models. Metrics for evaluating journals are defined, including impact factor, eigenfactor, h-index, and quartiles. The differences between Scopus and Web of Science databases are outlined. Tools for preliminary journal searches like Ulrich's and journal finder databases are recommended. The presentation emphasizes understanding journal metrics and selection criteria before submitting to ensure matching research with a suitable publication outlet.
Exploring The Dimensions and Dynamics of Felt Obligation: A Bibliometric Anal...AJHSSR Journal
ABSTARCT: This study presents, to our knowledge, the first bibliometric analysis focusing on the concept of
"felt obligation," examining 120 articles published between 1986 and 2024. The aim of the study is to deepen our
understanding of the existing knowledge in the field of "felt obligation" and to provide guidance for further
research. The analysis is centered around the authors, countries, institutions, and keywords of the articles. The
findings highlight prominent researchers in this field, leading universities, and influential journals. Particularly,
it is identified that China plays a leading role in "felt obligation" research. The analysis of keywords emphasizes
the thematic focuses of these studies and provides a roadmap for future research. Finally, various
recommendations are presented to deepen the knowledge in this area and promote applied research. This study
serves as a foundation to expand and advance the understanding of "felt obligation" in the field.
KEYWORDS: Felt Obligation, Bibliometric Analysis, Research Trends
This document discusses journal prestige and metrics for comparing journals. It begins by asking why discerning journal quality is important given the increasing number of journals. Common metrics for comparing journals that are discussed include impact factor, h-index, SCImago journal rank, and usage. The document recommends that in choosing a journal to submit one's research, one should consider the significance and scope of their work, as well as the aims, scope, subject area, prestige, editors, speed, audience, and coverage of different journals.
Similar to Impact factors-the basics-cross_uksg (20)
This document describes a study comparing 48 patients clinically diagnosed with semantic dementia (SD) to patients with progressive nonfluent aphasia (PNFA), behavioral variant frontotemporal dementia (bvFTD), and Alzheimer's disease (AD) based on speech, comprehension, naming, repetition and behavioral features. Key findings include:
1) Patients with SD had significantly lower scores on naming and comprehension tests compared to other groups and their speech fluency was between PNFA and AD/bvFTD.
2) Semantic substitutions were frequent in SD but phonological errors were absent, unlike PNFA. Questioning the meaning of words was seen in nearly all SD patients.
3) Behavioral
The ever increasing costs of journal subscriptions are forcing libraries to use more data-driven methods for cancellations and collection management. This article describes using citation analysis of faculty publications to measure citations to journals in a library's collection. At a cancer research institute in the Netherlands, over 200 journal titles were analyzed. About 10% of titles showed extremely low citation scores (<10 articles) and were considered for cancellation proposals to reduce costs. Citation data from research publications can provide objective data to inform decision-making about the journal collection.
हिंदी वर्णमाला पीपीटी, hindi alphabet PPT presentation, hindi varnamala PPT, Hindi Varnamala pdf, हिंदी स्वर, हिंदी व्यंजन, sikhiye hindi varnmala, dr. mulla adam ali, hindi language and literature, hindi alphabet with drawing, hindi alphabet pdf, hindi varnamala for childrens, hindi language, hindi varnamala practice for kids, https://www.drmullaadamali.com
Leveraging Generative AI to Drive Nonprofit InnovationTechSoup
In this webinar, participants learned how to utilize Generative AI to streamline operations and elevate member engagement. Amazon Web Service experts provided a customer specific use cases and dived into low/no-code tools that are quick and easy to deploy through Amazon Web Service (AWS.)
Communicating effectively and consistently with students can help them feel at ease during their learning experience and provide the instructor with a communication trail to track the course's progress. This workshop will take you through constructing an engaging course container to facilitate effective communication.
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
1. The E-Resources Management Handbook Jo Cross Impact factors – the basics
Impact factors – the basics
JO CROSS
Market Research Manager
Taylor & Francis
The E-Resources Management Handbook – UKSG
This chapter is designed to be an introduction to impact factors and how they are
calculated. It goes on to look at some of the major issues that need to be consid-
ered when evaluating journal impact factors.The chapter considers implications
of the cause and effect of subject differences in impact factors and different
article types such as news items, editorials and review articles.The paper also
considers the skewed distribution of citations to articles within a journal and the
relationship between journal size and impact factor changes between years.
What are impact factors?
At the simplest level, journal impact factors give the average number of citations to articles in a particular
journal; essentially, the average number of times that articles in a journal are referenced by other articles.
Impact factors were conceptualized by Eugene Garfield and Irving H Sher in the 1960s as an aid to
evaluating journals for inclusion in Current Contents® and the Science Citation Index® 1, 2.
An average citation measure was needed to account for the effects of the size and age of a journal on
the total number of citations it receives. Older and larger journals will generally receive more citations
because they have larger bodies of previously published articles available to be cited.
Calculating an impact factor requires a denominator (the total number of articles published) and a
numerator (the total number of citations to those articles). A time period, or ‘window,’ needs to be defined
for both of these variables.
The publication window is the period during which the articles included in the calculation were
published. The citation window is the period during which citations to these articles were counted.
Today, the term ‘impact factor’ most commonly refers to figures calculated and published by Thomson
Reuters each year in the Science and Social Sciences Editions of the Journal Citation Reports (JCR). Thomson
had acquired ISI and all its products in 1992 and merged with Reuters in 2008 to form Thomson Reuters.
These figures give a two-year impact factor and use very specific publication and citation windows. The
citation window here is the impact factor year, and the publication window refers to the two previous
years. Therefore, the 2007 JCR impact factors (released in 2008) were calculated as follows:
number of citations in 2007 to articles published in 2005 and 2006 in Journal X
number of articles published in 2005 and 2006 in Journal X
For example, the 2007 impact factor for Advances in Physics was calculated as follows:
Citations in 2007 to articles published in Advances in Physics in 2005 = 115
Citations in 2007 to articles published in Advances in Physics in 2006 = 86
Total citations received in 2007 to articles published in 2005 and 2006 = 201
Number of articles published in Advances in Physics in 2005 = 12
Number of articles published in Advances in Physics in 2006 = 9
Total number of articles published in 2005 and 2006 = 21
1
2. Impact factors – the basics Jo Cross The E-Resources Management Handbook
citations in 2007 to articles published in 2005 and 2006
2007 impact factor =
number of articles published in 2005 and 2006
201
2007 impact factor for Advances in Physics = = 9.571
21
For the rest of this article ‘impact factor’ will refer to the two-year JCR impact factor unless stated otherwise.
The use of the JCR model has the following implications:
■ each article published is included in the denominator for two impact factor years (the two years after
the year of publication). Thus, an article published in 2005 will be included in both the 2006 and 2007
impact factors
■ citations received in the year of publication or in the third year after publication or later will not count
towards any impact factor calculation.
Impact factors have been adopted for use as measures of journal quality based on the premise that: “the
value of information is determined by those who use it” 3, the idea being that the value of a journal can be
measured by the number of times its use is formalized in the form of a citation. Thomson Reuters has
suggested that impact factors can be useful tools for the management of library journal collections. There
are, however, several issues associated with the use of impact factors as measures of quality and it is
important to understand these before utilizing impact factor data in any decision-making process. The rest
of this chapter will look in some depth at many of these issues.
Subject variation in impact factors
The average number of citations to articles during the two years after publication varies considerably
across different subject fields. This leads to impact factors of very different magnitudes between fields, as
illustrated in Figure 1. The impact factors plotted here are calculated by counting the number of citations
in the current year to articles published by all journals in the category in the two previous years then
dividing this by the total number of these articles. Thus, these figures represent the average number of
times an article in the field has been cited: the impact factor of the entire category.
JCR category
Category aggregate impact factor
Figure 1. Impact factors for 15 categories from the 2007 JCRs
2
3. The E-Resources Management Handbook Jo Cross Impact factors – the basics
The 15 categories shown in Figure 1 are from a very wide range of fields from both the Science and
Social Sciences Editions of the JCR. However, even within a more closely-related group of subject
categories, there can be high variation in impact factors. This is illustrated in Figure 2, which shows the
category impact factors for nine sub-fields within physics.
JCR category
Category aggregate impact factor
Figure 2. Impact factors for nine physics categories from the 2007 JCR Science Edition
What causes subject variation in impact factors?
Subject variations in impact factor are due to both different levels and patterns of citation activity between
journals in different fields. Figure 3 shows the general magnitude of citation levels after publication for six
subject categories. As shown here, there are major differences in the number of citations to articles in each
Figure 3. Subject variation in citation levels after publication
3
4. Impact factors – the basics Jo Cross The E-Resources Management Handbook
of the different subject areas, with those in cell biology, for example, receiving many more citations at all
points after publication than those in economics or maths.
One possible reason for higher citation levels in some fields is variation in the average number of
authors per article. There is some evidence that highly-cited articles tend to have more authors4 and that
subject fields with more authors per paper tend to have higher impact factors5. This is probably due to the
tendency of authors to cite their own work and that of their research team.
Varying publication behaviours in different subject fields also contribute to differing levels of citations;
for example, in many of the social sciences greater use is made of books as a method of dissemination than
in the hard sciences. This means that a relatively high proportion of references from journal articles in
these fields go to books6, reducing the total number of inter-journal citations. Equally, many of the citations
in these fields may come from references within books and these are mostly not captured by Thomson
Reuters7,8. In engineering a similar effect occurs with many citations going to material published in
conference proceedings rather than in traditional journals9.
Applied fields also differ from basic research fields in terms of the total number of citations. Journals in
applied fields are more likely to reference journals in related basic research fields than other applied
journals. There is no comparable flow of citations back from the basic research journals. Thus, basic
research fields tend to receive more citations than related applied fields and, therefore, have higher impact
factors. For example, journals in basic medicine fields generally have higher impact factors than those in
clinical medicine fields10. We can also see from Figure 2 that the applied physics category has a relatively
low impact factor compared to most of the other physics categories.
A difference in the level of coverage by Thomson Reuters across subject fields is another major
contributor to varying magnitudes of citation activity as measured by the JCR11. Citation data in the JCR
comes only from publications that are indexed by Thomson Reuters. Figure 4, which is based on data from
Ulrich’s Periodicals Directory, illustrates the different levels of coverage of journals by Thomson Reuters
across broad fields. Science subjects are in blue and social science and humanities subjects in yellow.
* Does not include titles only listed in the Arts & Humanities Citation Index
Figure 4. Percentage of active, refereed, academic/scholarly titles covered in the JCR by subject, according to Ulrichs (June 2008)
The source list for citations in the JCR is slightly broader than the journals covered within, additionally
incorporating any citations from titles covered in the Arts & Humanities Citation Index, ISI Proceedings
and the Biosis database. However, these additional sources do not compensate for the different levels of
coverage across fields.
4
5. The E-Resources Management Handbook Jo Cross Impact factors – the basics
In subject fields with lower coverage, a higher proportion of citations from the field will not be captured
in the JCR data set and this will lead to lower recorded citation levels. Figure 4 illustrates generally low
coverage in social science fields and this is likely to be a contributing factor towards lower recorded
citation levels and therefore lower impact factors in the social sciences JCR.
In addition to different levels of recorded citation activity between fields, different citation patterns also
affect the magnitude of impact factors. Figure 5 shows the percentage of lifetime citations received by year
since publication for the same six subject categories. As mentioned earlier, only citations received in the
two calendar years after publication count towards an impact factor. These citations are those that fall
within the impact factor window as shown in blue in Figure 5.
Figure 5. Subject variation in citation distributions
Figure 5 clearly illustrates that the proportion of citations falling within the impact factor window varies
considerably between subject areas. Approximately 22% of lifetime citations to cell biology articles fall
within this window compared to only around 8% of citations to articles in economics or maths. This
compounds the difference in impact factors between these fields since cell biology articles not only receive
more citations in total, but a higher proportion of these contribute towards impact factors.
Why a two-year impact factor?
As mentioned earlier, impact factors were originally devised to help with journal selection for inclusion in
Current Contents products. At the time of the inception of impact factors, the primary fields of focus for
Current Contents were fields related to molecular biology and biochemistry12. In these fields, 25% of
citations received in a particular year were accounted for by articles published in that year and the two
previous years13. Thus, using a measure that only included citations to recent articles was considered
appropriate in this context.
A similar pattern of citations can still be seen in these and other fast-moving fields, as illustrated by the
pattern of citations (the ‘citation curve’) for cell biology in Figure 5. However, since the citation curve is
clearly not the same for all fields, many commentators have argued for the publication of more long-term
impact measures that would take into consideration a greater proportion of lifetime citations for slower-
moving fields14, 15.
Thomson Reuters justifies its continued publication of two-year impact factors on the basis of two main
characteristics of this particular metric: it is both current and responsive16. Using citations in the current
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6. Impact factors – the basics Jo Cross The E-Resources Management Handbook
year (where ‘current year’ refers to the impact factor year rather than the year of JCR publication, which
is the year after) and articles in the two previous years ensures that JCR impact factors are highly sensitive
to recent changes in citation activity.
For example, a journal’s JCR impact factor will respond to papers or topical issues that receive an
abnormally high number of citations, but will not be skewed for more than two years. Using a longer
publication window would dilute these effects but would include them for a longer period. Thomson
Reuters considers this sensitivity to be one of the strengths of the JCR impact factor. However, it could also
be considered a weakness since it means that several years of impact factors need to be considered to
gauge the general impact of a title.
Another advantage of the JCR impact factor is that it only requires three years’ worth of data (two
publication years and one citation year) to calculate. Alternative metrics that have been suggested, such
as five- or seven-year impact factors, would take over twice as long to produce. Considering the
importance that has been, rightly or wrongly, assigned to impact factors, this extended delay could be
highly detrimental to new journals trying to establish themselves.
Currently, the two-year measure continues to be the only official impact factor published in the annual
JCR. Thomson Reuters, however, does acknowledge that a longer-term impact measure may be more
appropriate in some fields and recent communications with Thomson Reuters’ staff suggest that a five-
year measure may be included in a forthcoming update to the 2007 JCR.
In the meantime, a couple of ways in which a five-year measure can be calculated from data available
in the JCR have been suggested17,18. Extended impact measures for journals can also be calculated from
data available in another Thomson Reuters product, the Journal Performance Indicators19. This product
allows comparison to field-specific baselines.
Consequences of subject variations in impact factors
The high variation in average impact across different subject areas means that impact factors cannot be
used to compare journals from different subject areas. This is why the journals covered by the JCR are
classified into fairly narrow subject categories. It is only at this level that journals should be ranked
according to their impact factors.
Even within the JCR subject categories some journals will have a subject advantage over others, for
example, where a subject category contains both basic research and applied journals – practice-based and
educational journals often have particularly low impact factors compared to the basic research journals
listed in the same categories. There can also be a subject advantage in categories which are
multidisciplinary by nature, for example, social science journals such as the Journal of Sports Management
and Journal of the Philosophy of Sport in the sports sciences categories tend to rank lower than the majority
of the sports medicine titles in the same category. All these factors need to be considered when comparing
journal rankings within a subject category.
Subject variation in impact factors is also one of the reasons it is unwise to create an ‘average impact
factor’ for a publisher’s entire list of journals. Now that many publishers offer ‘bulk sales deals’ it can be
tempting to try and gauge the quality of such an offering by creating an average impact factor for the
journals included in the deal. However, if subject differences mean that the impact factors of journals from
different fields cannot be compared, then it follows that the data should not be combined either. This sort
of publisher-wide averaging of impact factors will always favour publishers with strong life sciences
programmes over those with stronger social science programmes. Since impact factors can vary even
between quite closely related fields, as shown in Figure 2, averaging impact factors across even a single
subject package is unlikely to give a fair view of the quality of the package. The same is true of trying to
compare publishers on the basis of price per impact factor where journals from multiple JCR categories
are included in the analysis, for example, the LISU report on ‘Trends in Scholarly Journal Publishing’,
which combines such diverse categories as educational psychology and cell biology (which have 2007
category aggregate impact factors of 1.154 and 5.603, respectively) into one analysis on biomedical titles20.
6
7. The E-Resources Management Handbook Jo Cross Impact factors – the basics
Is every published item counted?
Many journals publish non-substantive items such as news articles, editorials, letters to the editor and
meeting abstracts, often referred to as ‘non-source items’. These items are usually never cited and, so that
journals publishing this material are not unduly penalized, they are not counted in the article total
(denominator) for JCR impact factor calculations.
Although these ‘non-source items’ are rarely cited, there are exceptions and, interestingly, these
citations do count towards the citation total (the numerator of the calculation). This discrepancy between
what is counted in the two halves of the calculation arises due to the method used by the JCR division at
Thomson Reuters to count citations to a journal.
The system searches the reference lists of articles published in the impact factor year for journal titles
and publication years only. Citations are not matched to individual published items and for that reason
the system does not differentiate between citations to source items and those to non-source items. So, for
example, in the reference below, the JCR would record a citation to the 2005 volume of Contemporary
Physics but would not capture any more detailed information about the actual article that had been cited.
BIER, M. (2005) Modelling processive motor proteins: moving on two legs in the microscopic realm.
CONTEMPORARY PHYSICS 46: 4.
Other departments at Thomson Reuters do match citation data at the individual article level and this
information is used to compile products such as ISI Journal Performance Indicators (JPI) and Essential Science
Indicators SM. The data used in the JCR, however, continues to be collected at the journal level.
The consequence of this discrepancy is that journals publishing a large number of ‘non-source items’
(this is more common in some fields, such as medicine) or journals publishing particularly interesting
‘non-source items’ can have artificially inflated JCR impact factors. For these journals, citations are being
counted in the numerator to articles that are not counted in the denominator. These citations can be
considered to be ‘free’ citations.
The number of non-source items published by particular journals can be found under the heading
‘Journal Source Data’ in the JCR. The number of ‘other items’ here refers to the number of non-source
items. This does not, however, give an indication of the number of citations these articles have received.
Review articles
Review articles, i.e. articles that attempt to sum up the current state of research on a particular topic, are
generally cited more often than primary research articles. This is because authors will often cite one review
article rather than the many primary research articles it is based on. Therefore review journals, or journals
that publish a significant amount of review content alongside their primary content, usually have higher
impact factors than other journals in their field. For example, analysing data from the 2007 JCR shows that
the aggregate 2007 impact factor for science journals publishing over 75% review articles is over 2.5 times
higher than the figure for the remaining journals.
Although the JCR lists journals from different subject areas separately to take account of subject
variation in its impact factors, it does not list review journals separately from primary journals. Therefore
review journals and journals containing a high proportion of review content are often ranked amongst the
highest journals in their fields. For instance, the top three journals in the 2007 toxicology category are
review journals and the fourth ranked journal publishes over 25% review articles. The JCR also includes
figures on the number of review articles published by each journal that it covers in the ‘Journal Source
Data’ section. It is important to consider the proportion of review content when comparing the impact
factors of different journals.
The variance in citation rates to different types of journals and journals with a different mix of articles
is another reason why it is unwise to calculate average impact factors across publisher lists. Publishers
with a large list of review journals will generally fare better in such comparisons.
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8. Impact factors – the basics Jo Cross The E-Resources Management Handbook
Skewed distribution of citations
Impact factors are designed to be “a measure of the frequency with which the ‘average article’ in a journal has
been cited in a particular year” 21. However, the distribution of citations to articles within a journal is
generally highly skewed with a minority of articles receiving the majority of citations especially within the
narrow impact factor windows22,23,24.
Figure 6. Distribution of citations in 2007 to articles published in 2005 and 2006 for a journal with an impact factor of 4.651
This type of skew is clearly illustrated in Figure 6, which shows the distribution of citations in 2007 to
articles published in 2005 and 2006 for a journal with an impact factor (mean number of citations) of 4.651.
In this case over 80% of articles have less than the mean number of citations, while over 40% have zero
citations within this window. Here the mean is particularly skewed by one article which received 73
citations.
What this means is that the impact factor often does not actually give a good indication of the frequency
with which the ‘average article’ has been cited. There have been calls for Thomson Reuters to produce a
median-based average for journals along with the mean25 but this would not be possible without a change
in the way the data is collected for the JCR. Data is currently collected at the journal level (see Is Every
Published Item Counted?) above and therefore measures which rely on distribution data such as medians
cannot be calculated from the current data set.
Journal size and impact factor variability
Impact factors can be highly variable from year to year, however, it is important not to read too much into
subtle changes in these figures, especially in smaller journals.
Impact factors can be thought of as the mean number of citations to a biased sample of articles from the
population of all articles in that field26. Statistically, smaller samples will have greater sampling errors than
larger ones; that is, the mean values delivered by repeated sampling will be more variable. If we envisage
impact factors as repeated samples from the same population of articles, then we would expect the impact
factors of smaller journals to be more variable, year on year, than those of larger journals.
Figure 7 shows the median change in JCR impact factor (either up or down) between 2006 and 2007, for
all journals in both JCR editions, grouped by journal size. This clearly illustrates that smaller journals have
more variable impact factors, on average, than larger ones.
8
9. The E-Resources Management Handbook Jo Cross Impact factors – the basics
Figure 7. Median change in impact factor between 2006 and 2007 by journal size
Another way to look at this is to consider that a very small change in the total number of citations to a
journal that publishes relatively few articles a year will lead to quite a high percentage change in the
impact factor between years. This is especially true when we look at journals that have relatively low
impact factors to start with. For example, it only takes two extra citations to a journal with an impact factor
of 0.500 which publishes 20 articles a year (and so would have an impact factor denominator of 40) to
increase its score to 0.550, a 10% increase. Compare this to a much larger journal publishing 100 articles a
year with an impact factor of 4.000. This title would need to gain an extra 80 citations to see a 10% increase
to 4.400.
It is important to bear this caveat in mind when evaluating any changes in JCR impact factor between
two years. If a journal is very small, then a relatively large change in impact factor (or a consistent increase
or decrease over several years) is required to demonstrate that there has been an underlying change in the
population from which the journal draws its articles.
In addition to averaging impact factors across a list, it can be tempting to calculate the mean percentage
increase of a group of titles in an attempt to gauge the improvement of the list as a whole. However, the
high variability in impact factor is one reason to avoid this approach. In the theoretical examples given
above, both journals see an increase of 10% for very different changes in the actual number of citations
received between the two years. Both these changes would be given exactly the same weight in a simple
average of the percentage changes in impact factors across a list.
There is also a definite increase bias in such a calculation. Table 1 illustrates how increases are given a
much higher weight in mean percentage change calculations. Suppose that two theoretical journals both
publish 20 articles per year, giving both titles an impact factor denominator of 40 (2 x 20), and that one title
gains six citations and the other loses six. The average absolute change in impact factor is zero but the
mean percentage change is +45% because the increase in citations leads to a 150% increase in impact factor
compared to only a 65% decrease for the loss of citations.
This is an extreme and hypothetical example, but the principle holds across all increases and decreases.
It is worth bearing in mind that the highest possible percentage decrease for a journal is –100%, but there
Citations IF year 1 Citations IF year 2 Absolute Change % Change
year 1 year 2 in IF in IF
Journal A 4 0.100 10 0.250 +0.150 +150%
Journal B 10 0.250 4 0.001 –0.150 –65%
Average Change 0 +45%
Table 1. Illustration of the increase bias in mean percentage change calculations
9
12. Impact factors – the basics Jo Cross The E-Resources Management Handbook
Biographical note
Jo graduated from Oxford University with a BA (Hons) in Experimental Psychology. She started her career
in academic journal publishing at Elsevier where she worked in various roles including author support,
journal management (Editorial) and as a Publishing Information Manager. Jo moved to Taylor & Francis
in 2004 to set up and run the Market Research Department.
Studying and analysing citation and impact factor data has been a large component of Jo’s role since
she became a Publishing Information Manager in 2002. In 2007 she ran a briefing session on Impact Factors
at the annual UKSG conference.
To view more chapters from The E-Resources Management Handbook, published by UKSG, click here:
http://www.uksg.org/serials/handbook.asp
12