There are several simple and sophisticated scientometric indicators generally applied in the literature (e.g. total number of publications and citations, citations per journal paper, relative citedness indexes, Hirsch index, etc.), which may characterize the publications of scientists both qualitatively and quantitatively. The calculation methods generally use data referring to the total set of...

A Letter to the Editor shortly summing up ten or so years of research into the h-index.

using bibliographic records from the social science citation index, science citation index, and arts & humanities citation index, this paper tries to give a complete view of the evolution of the field of scientometrics based on its literature published during 1980 to 2009. this is a descriptive survey using scientometric indicators. findings revealed that out of 691 articles in the field of sci...

purpose: the purpose of this study was to establish scientometrics departments in the iranian academic libraries based on the swot model. methodology: this is an applied study carried out by the survey method. the study population included 80 librarians of mashhad universities. data collection was based on the statistical distribution of the questionnaire following the swot model. findings: the...

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Scientometrics is the field of quantitative studies of scholarly activity. It has been used for systematic studies of the fundamentals of scholarly practice as well as for evaluation purposes. Although advocated from the very beginning the use of scientometrics as an additional method for science history is still under explored. In this paper we show how a scientometric analysis can be used to ...

In a critical and provocative paper, Abramo and D’Angelo claim that commonly used scientometric indicators such as the mean normalized citation score (MNCS) are completely inappropriate as indicators of scientific performance. Abramo and D’Angelo argue that scientific performance should be quantified using indicators that take into account the productivity of a research unit. We provide a respo...

Measuring science is based on comparing articles to similar others. However, keyword-­‐based groups of thematically similar articles are dominantly small. These small sizes keep the statistical errors of comparisons high. With the growing availability of bibliographic data such statistical errors can be reduced by merging methods of thematic grouping, citation networks and keyword co-­‐usage.