Abstract
The increasing use of citation impact indexes for evaluation and comparison not only of individual researchers but also of institutions, universities and even countries has prompted the development of new citation metrics. Currently, the number of publications and citations is widely accepted as an easy and balanced way to compare scientists. Calculation of such statistics depends on the availability of a comprehensive database of publications and their citations. Google Scholar aims at providing such a service and is currently the most widely used freely available search engine for scientific and academic literature. However, the citations generally used to calculate citation statistics include self-citations, which deviates from the intention of using citations as a reflection of research impact. To the best of our knowledge, there are no available tools for calculating citation statistics that account for self-citations. We present a web-based service CIDS (Citation Impact Discerning Self-citations), that takes into account self-citations. An assessment of CIDS in a research team has shown that both the number of citations and the h-index is sensitive to self-citations at the individual level, the h-index increasing 24% on average when considering them. However, self-citation is highly variable among individuals and its contribution highly variable. We conclude that at the individual and research unit level, self-citations are not dismissible when calculating citation statistics. Even the h-index is influenced by self-citation and comparing individuals without taking them in account can produce misleading results.
| Original language | English (US) |
|---|---|
| Journal | Cybermetrics |
| Volume | 13 |
| Issue number | 1 |
| State | Published - Jul 17 2009 |
| Externally published | Yes |
ASJC Scopus subject areas
- Library and Information Sciences