Self-citation and corruption: cross-sectional, cross-country study - Alexander C. Tsai (Inishmore Laser Scientific Publishing Ltd, 2021)
# Background Self-citation appears to be widely prevalent. However, the structural drivers of self-citation are poorly understood. # Methods Data for this study were obtained from a recently published study of Scopus data aggregated across all authors with \>5 publications, across all scientific fields, which yielded aggregate, country-level data on the mean co-author self-citation rate for the period 1960-2018. These data were merged with 2018 data from Transparency International on corruption, and additional data extracted from the World Development Indicators. The country-level association between the self-citation rate and the corruption index was estimated using multivariable linear regression. # Results Across 178 countries, the correlation between the mean self-citation rate and the corruption index was -0.52, 95% confidence interval, CI=-0.62 to -0.41. Among the 49 countries in the lowest quartile of the corruption index, the mean self-citation rate was 0.24 (standard deviation, SD=0.06). Among the 44 countries in the highest quartile of the corruption index, the mean self-citation rate was 0.21 (SD=0.05). In a weighted linear regression model with robust estimates of variance, the corruption index had a statistically significant association with the mean self-citation rate (2nd quartile compared with 1st quartile: *b*=-0.08 (95% CI=-0.17 to -0.01); 3rd quartile: *b*=-0.11 (95% CI=-0.19 to -0.02); 4th quartile: *b*=-0.10 (95% CI=-0.19 to -0.01; N=165). The implied effect size was large in magnitude and robust to potential confounding by unmeasured covariates. # Conclusions In this cross-sectional, cross-country analysis, there was a strong correlation between a country's overall level of corruption and the mean self-citation rate. The estimated association was statistically significant, large in magnitude, and unlikely to be explained away by unmeasured confounding. Better understanding of how corruption norms evolve is likely to be critical in addressing the problem of extreme self-citation and other forms of citation manipulation.