Author Level Metrics
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The document discusses author level metrics and how they are used to measure the impact of individual authors. It defines author level metrics as citation metrics that measure the bibliometric impact of individual researchers. It also discusses different types of author level metrics, including article-level metrics, journal-level metrics, h-index, i10-index, g-index, and altmetrics. Finally, it discusses tools that can be used to measure author metrics, such as Google Scholar, Web of Science, Scopus, and Publish or Perish.
Author Level Metrics
- 1. Dr. Mallappa Vijayakumar MSc., MCA., PhD. University Librarian CENTRAL UNIVERSITY OF RAJASTHAN राजस्थानके न्दरीयविश्िविद्यालय
- 3. Author level metrics is a system/standard for measuring the authors or evaluation of authors. Author-level metrics are citation metrics that measure the bibliometric impact of individual authors, researchers, academics, and scholars. Other metrics originally developed for academic journals can be reported at researcher level, such as the author-level eigenfactor and the author impact factor. Author Level Metrics
- 4. Project Grants Invited Speaker Consultancy Career Advance Benefit of Author Level Metrics
- 5. Author level Metrics can be categorized in to Article-level metrics Journal-level metrics H-index, i10-index, g-index, Altmetrics and others Scientometrics Category
- 6. There are several measures of author impact. They include Total number of publications Total number of citations for all publications Average number of citations Number of citations for a particular publication Number of citations for a particular period Number of reading/visit Number of downloads Number of request for the articles Article Level Metrics
- 7. There are several ways to measures the Journal Journal Impact Factor SCImago Journal Ranking And others Journal Level Metrics
- 8. Journal impact factors are found in Journal Citation Reports (JCR). JCR is a unique database which is used to determine the relative importance of journals within their subject categories. An impact factor is one measure of the quality of a journal. This is calculated by the number of citations received by the journal, from other journals within the database. Journal Impact Factor Number of citation received by “X” Journal in “A” the year Journal Impact Factor = Number of article published by same “X” Journals in previous two years of “A”
- 9. Five things to know about impact factors Not all journals have impact factors. They must be indexed in the database like Web of Science to have an impact factor A journal has only one impact factor, but it may be listed in more than one category A journal impact factor should not be looked at in isolation, but in comparison to other journals in the same category Impact factors vary across disciplines A five-year impact factor may also be used in some disciplines. Journal Impact Factor
- 10. SCImago journal Ranking SCImago Journal uses Scopus database to compare journals. It is freely available on the web. The Journal Rankings tab allows you to retrieve a list of journals within a subject area or category. SCImago Journal Rank (SJR indicator) is a measure of scientific influence of scholarly journals that accounts for both the number of citations received by a journal and the importance or prestige of the journals where such citations come from. A journal's SJR is a numeric value indicating the average number of weighted citations received during a selected year per document published in that journal during the previous three years. Higher SJR values are meant to indicate greater journal prestige. SJR is updated twice a year.
- 11. h-index The h-index is a popular metric. It was developed by J.E. Hirsch, a physicist at the University of California. An index to quantify an individual's scientific research output i.e., 'An entity has an h-index value of y if the entity has y publications that have all been cited at least y times'. (Hodge & Lacasse). Thus, the h-index reflects both the number of publications and the number of citations per publication. The index is designed to improve upon simpler measures such as the total number of citations or publications. The index works properly only for comparing scientists working in the same field; citation conventions differ widely among different fields.
- 12. i10-index The i10-Index, used solely by Google Scholar, was introduced in July 2011. It calculates the number of academic publications an author has written that have at least ten citations from others. This is one way to gauge the productivity of an author. i10-Index = the number of publications with at least 10 citations.
- 13. g-index Harzing's Publish and Perish Manual explains the g-index is calculated based on the distribution of citations received by a given researcher's publication. A set of papers has g-index , if g is the highest rank such that the top g papers have together at least g2 citations. Also means that, the top g+1 papers have less than (g+1)2 papers. For example: If an author is having g-index of 20 means that author has published at least 20 articles that combined have received at least 400 citations. One of the main advantages of the g-Index is the inflated values of this index helps give credit to lesser cited or non-cited work whilst attributing credit for highly-cited papers.
- 14. Altmetrics 'Altmetrics is the creation and study of new metrics based on the Social Media Tools for analyzing, and informing scholarship' Altmetrics (alternative metrics) has emerged due to the limitations of traditional citation metrics such as the impact factor, providing complementary evidence of research impact. 'Altmetrics' is a very broad category that includes diverse measures that can range from a news story to a Facebook like. If you have an account or profile with any social network service (Flickr, Facebook, Academia.edu, etc.), you will be familiar with 'likes', 'downloads', 'views', 'shares' and similar indications of interest in your activity.
- 15. Altmetrics Pros Cons Immediacy Unlike citations, which take time to accumulate, impact can be assesed in real-time Potential for manipulation The openness of social media provides the opportunity for artifical inflation of figures Track impact outside the formal publishing network Can measure the impact of a wider variety of scholarly communication channels such as datasets, presentation slides, pre-prints, videos and websites Popularity of social media services Comparisons of figures from a specific tool (e.g. Twitter) for material published at different times can be affected by fluctuations in the number of users Assess reach beyond scholarly citing community Capture evidence of engagement in broader society e.g. practitioners, undergraduates, general public including the impact of influential but uncited work Acceptance These measures and their role in measuring impact are evolving and have differing levels of acceptance in the scholarly community
- 16. Publish or Perish is a software program created by Anne-Wil Harzing of University of Melbourne. The program analyses your Google Scholar raw citations and presents you with a variety of statistics, including • total number of citations • total number of references • average number of references • h-index • g-index Publish or Perish
- 17. Degree of Collaboration Lotka’s Law and others Scientometrics
- 18. The degree of collaboration is defined as the ratio of the number of collaborative research papers to the total number of research papers in the discipline during a certain period of time(Subramanyam). It is expressed as Nm C = Nm+Ns where; C is the degree of collaboration in a discipline. Nm is the number of multi-authored research papers in the discipline published during a year. Ns is the number of single authored research papers in the discipline published during a year. Degree of Collaboration
- 19. Lotka’s law describes the frequency of publication by authors in any given field. It states that the number of authors making ’x’ contributions in a given period is a fraction of the number making a single contribution, the formula ”1/xa” where a nearly always equals two, i.e., an approximate inverse-square law, where the number of authors publishing a certain number of articles is a fixed ratio to the number of authors publishing a single article. As the number of articles published increases, authors producing that many publications become less frequent. There are 1/4 as many authors publishing two articles within a specified time period as there are single-publication authors, 1/9 as many publishing three articles, 1/16 as many publishing four articles, etc. Though the law itself covers many disciplines, the actual ratios involved (as a function of 'a') are discipline-specific. The general formula says XnY=C or Y=C/Xn, where X is the number of publications, Y the relative frequency of authors with X publications, and n and C are constants depending on the specific field (n~2). Lotka’s Law
- 20. Requirement for Author Metrics To assess the we need Digital Author ID like; • ORCID ID • Scopus ID • Researcher/ Publon ID • Google Scholar ID • Others
- 21. Tools for Author Metrics There are many tools to assess the Author Metrics • Google scholar • Web of Science • Scopus • Publish or perish • And others
- 22. Conclusion It is worth remembering that the key measuring tools (databases) only gather data from the journals they index. Author naming inconsistencies can lead to missed citations Citation culture varies across discipline and not be comparable Publication Culture Researcher career is have different stages Author metrics Impact does not always equal to excellence Scholarly communication is evolving beyond the citations Factors affecting citation rates include type of article (eg review articles are more highly cited than editorials), Language, Refutation, Citation bias or self-citation, Subject area, Publication schedule, Journal reputation
- 23. Mail to librarian@curaj.ac.inCall to +91-9430702887
- 24. CENTRAL UNIVERSITY OF RAJASTHAN राजस्थानके न्दरीयविश्िविद्यालय Dr. Mallappa Vijayakumar MSC., MCA., PhD. University Librarian