Location: Crop Improvement and Protection ResearchTitle: Analysis of bibliometric indicators to determine citation bias Author
Submitted to: Palgrave Communications
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/28/2015
Publication Date: 6/2/2015
Citation: Simko, I. 2015. Analysis of bibliometric indicators to determine citation bias. Palgrave Communications. doi: 10.1057/palcomms.2015.11.
Interpretive Summary: Publications from 1995 throughout 2004 were analyzed to determine if the plant species used in research studies influenced the number of citations that papers received. Bibliometric data of papers from 108 plant species were obtained for the research fields of Genetics & Heredity, Physiology & Biology, Pharmacology, Toxicology & Pharmaceutics, Plant Pathology, and a Crop Science journal. The key findings of the current analyses are: 1) differences among citations of plant species from the same research field (or journal) are highly significant; 2) the more publications about a species, the higher the average citation score for the five most prominent papers of the species; 3) a fast growth in the number of publications of a species leads to a high average citation score of the species; 4) plant model species (including Arabidopsis thaliana) have citation scores higher than the overall mean for the research field, 5) Funnel plot analysis is a convenient method to analyze citation data, and 6) computer simulations can approximate citations of the most prominent publications of a species.
Technical Abstract: Publications from the 1995 to 2004 period (and cited throughout July 2013) were analyzed to determine if the plant species used in research studies influenced the number of citations that papers received. Bibliometric data of papers from 108 plant species were obtained for the research fields of Genetics & Heredity (G&H), Physiology & Biology (P&B), Pharmacology, Toxicology & Pharmaceutics (PTP), Plant Pathology (Path), and a Crop Science (CSw) journal. Funnel plot analyses and computer simulations were used to identify plant species with significantly high or significantly low citation scores. Statistical analyses detected a substantial, species-related citation bias in all research fields. Tests of relationships between bibliometric indicators suggest that the citation bias could partially be attributed to the total number of published papers per species and to the growing popularity of species. Species with a fast growing number of publications in recent years (e.g. new model organisms) have generally a higher average number of citations per paper than is the overall mean for the research field. In contrast, the average number of citations received by the five most prominent papers of the species was strongly correlated with the number of published papers (it is, the combined publication output of laboratories working with the species).