Beyond CiteScore: Exploring Citation Concentration in Digital Humanities Journals
DOI:
https://doi.org/10.34256/Keywords:
Citation Inequality, CiteScore, Digital Humanities, Gini CoefficientAbstract
Average-based citation metrics such as CiteScore and the Journal Impact Factor are widely used to assess journal performance and to guide authors in selecting journals. However, these metrics obscure the internal distribution of citations across articles and therefore fail to capture citation inequality within journals. This study addresses this limitation by examining the degree of citation concentration in Digital Humanities (DH) journals using the Gini coefficient. Citation data for articles published in fifteen most prolific Scopus-indexed DH journals between 2018 and 2024 was extracted from the Scopus database. 87.75% of articles fall within the 1-50 citation cluster, while only a very small proportion of articles received more than 200 citations indicating a disproportionate influence of a small number of highly cited articles. The Gini coefficient values indicate a moderate to high level of citation inequality across all journals (Gini coefficient ranging from 0.532 to 0.674), with citations concentrated in a small proportion of articles. Digital Humanities Quarterly and AI and Society exhibited the highest levels of inequality. Spearman correlation coefficient for the four consecutive block-periods of four years ranged from (-0.172) to (-0.316) revealing an inverse relationship between CiteScore and the Gini coefficient. Journals with lower CiteScore values tend to exhibit higher citation concentration. It is recommended that citation databases provide Gini Coefficient values of journals as ready reference to help authors get a more nuanced understanding of journal-level citation patterns, thus helping them in better selection of journals.
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