This website includes Anne-Wil's areas of research and online papers, resources to assist with academic publishing and careers, assessment of research and journal quality, as well as software for citation analysis.
The Harzing.com blog includes posts on: academic publishing, doing research, academic etiquette, using the Publish or Perish software, academic careers, gender in academia, research focus, and positive academia. If you are an early of mid career academic, your best starting point might be the Working in academia page.
Harzing 39;s Publish Or Perish Software Download For Mac
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It adds an age-related weighting to each cited article, giving (by default; this depends on the parametrization) less weight to older articles. The weighting is parametrized; the Publish or Perish implementation uses gamma=4 and delta=1, like the authors did for their experiments. This means that for an article published during the current year, its citations count four times. For an article published 4 years ago, its citations count only once (4/4). For an article published 6 years ago, its citations count 4/6 times, and so on.
The Publish or Perish Book focuses on citation analysis of individual researchers, not groups or institutes. Several metrics may be calculated for scientists and for journals, including their number of publications and citations, average number of citations per publication and per author, and the h-index, a widely used characterization of citation impact. Harzing argues using practical examples that such indicators are good markers of a researchers' influence, and are useful in assessing applications for jobs, promotion and tenure, and for literature research and choosing a journal in which to publish.
Using Google Scholar as a data source is advantageous as it retrieves publications not covered by Thomson Reuters' Web of Science: books, edited volumes and 'grey' literature such as conference proceedings. Harzing explains how to analyse citations with Google Scholar, and discusses ways that citation patterns of early reports can be used to predict the later impact of journal articles derived from them. But there are inevitable problems in tying together varied data, such as matching conference proceedings with the subsequently published paper.
Another option (less popular than the other two) to find your H-Index is Harzin's "Publish or Perish" which can be found at -or-perish It requires you to download a program onto your device. Once you do, a chart similar to the one below appears (it might also be located on the taskbar along the bottom of your computer screen).
This study presents a bibliometric analysis of the publications on melatonin research from the Scopus database during the period 2015-2019. Based on the keywords used, which are related to melatonin in the article title, the study retrieved 4411 documents for further analysis using various tools. We used Microsoft Excel to conduct the frequency analysis, VOSviewer for data visualization, and Harzing's Publish or Perish for citation metrics and analysis. This study reports the results using standard bibliometric indicators such as the growth of publications, authorship patterns, collaboration, and prolific authors, country contribution, most active institutions, preferred journals, and top-cited articles. Based on our findings, there is a continuous growth of publications on melatonin research for 5 years since 2015. China was the largest contributor to melatonin research, followed by the United States. The Journal of Pineal Research published the most number of publications related to melatonin research. Our findings suggest that the role of melatonin in plant and food sciences, as well as in cancer, may in later years take over the clusters that earlier dominated melatonin research.
An h-index of 20 signifies that a scientist has published 20 articles each of which has been cited at least 20 times. Sometimes the h=index is, arguably, misleading. For example, if a scholar's works have received, say, 10,000 citations he may still have a h-index of only 12 as only 12 of his papers have been cited at least 12 times. This can happen when one of his papers has been cited thousands and thousands of times. So, to have a high h-index one must have published a large number of papers. There have been instances of Nobel Prize winners in scientific fields who have a relatively low h-index. This is due to them having published one or a very small number of extremely influential papers and maybe numerous other papers that were not so important and, consequently, not well cited.
Contending that Hirsch's H-Index does not take into account the "age" of an article, Sidiropoulos et al. (2006) came up with a modification, i.e. the Contemporary H-Index. They argued that though some older scholars may have have been "inactive" for a long period their h-index may still be high since the h-index cannot decline. This may be considered as somewhat unfair to older, senior scholars who continue to produce (if one has published a lot and already has a high h-index it is more and more difficult to incease the index). It may also be seen as unfair to younger brilliant scholars who have had time only to publish a small number of significant articles and consequently have only a low h-index. Hirsch's h-index, it is argued, doesn't distinguish between the different productivity/citations of these different kinds of scholars.
The solution of Sidiropoulos et al. is to give weightings to articles according to the year in which they're published. For example, "for an article published during the current year, its citations account four times. For an article published 4 year ago, its citations account only one time. For an article published 6 year ago, its citations account 4/6 times, and so on. This way, an old article gradually loses its 'value', even if it still gets citations." Thus, more emphasis is given to recent articles thereby favoring the h-index of scholars who are actively publishing.
Improve your publishing projects and writing tasks. Find and integrate proper academic citations. Use a variety of sources, including databases and engines like Google Scholar and Microsoft Academic Search. Extract raw citations, run their analysis, transfer, edit, and present the results.
Apart from that there are various tools are available for bibliometric analysis such as Bibexcel, R, and Citespaceand VOSviewer tool. VOSviewer tool has been developed by Nees Jan van Eck and Ludo Waltman and was introduced in a paper published in Scientometrics in 2010. Currently VOSviewer software is in fashion among researchers, which is considered one of the powerful tools for data visualization. By using VOSviewer, authors can draw co-citation maps and analyze co-authorship, keyword co-occurrence, citation, bibliographic coupling etc, in less time. This software also performs cluster analysis and creates social network maps for countries, affiliations and sources. There is a concept of density and overlay visualization in VOSviewer tool in which density visualization gives an idea of the main areas in a network of bibliometric and overlay density represents development over time. Data cleaning is also possible by using thesaurus files.
Frequently, JIMS Kalkaji organizes workshop and Faculty Development Program ( FDP) on Bibliometrics Analysis for researchers, students and academicians. So that they can get more exposure in terms of writing good and quality research papers to get publish in reputed journals.
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The H-index is the number of articles with at least h citations. Kim McDonald writes that the H-index for an author describes "a scholar with an index of h has published h papers each of which has been cited in other articles at least h times."
The purpose of the M-index (or M-quotient) is to measure productivity over time. To retrieve this metric, divide the H-index by the number of years you have been publishing research.
One commonly used impact metric for journals is the Journal Impact Factor (JIF or IF) score. It is an average of the number of times articles published in a particular journal have been cited in the two previous years.
Granger causality provides a framework that uses predictability to identify causation between time series variables. This is important to policymakers for effective policy management and recommendations. Granger causality is recognized as the primary advance on the causation problem. The objective of this paper is to conduct a bibliometric analysis of Granger causality publications indexed in the Web of Science database. Harzing's Publish or Perish and VOSviewer were used for performance analysis and science mapping. The first paper indexed was published in 1981 and there has been an upward trend in the annual publication of Granger causality studies which are shifting towards the areas of environmental science, energy, and economics. Most of the publications are articles and proceeding papers under the areas of business economics, environmental science ecology, and neurosciences/neurology. China has the highest number of publications while the United States has the highest number of citations. England has the highest citation impact. This paper also constructed country co-authorship, co-analysis of cited references, cited sources, and cited authors, keyword co-occurrence, and keyword overlay visualization maps. 006ab0faaa