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What makes articles highly cited? A bibliometric analysis of the top 1% most cited research in applied linguistics(2000-2022)
Citation counts, although controversial, have long been used as a yardstick for research evaluation. The normative view regards citing as a means to credit scientific contributions, so the number of citations reflects not only scholarly attention but also research quality. However, the application of social constructivist theory introduces a nuanced perspective, asserting that a variety of factors unrelated to scientific merit can potentially influence citation counts. This dual nature of citation practices has been widely discussed across disciplines, yet it remains an underexplored domain in applied linguistics. This bibliometric study, with a particular interest in highly cited papers, aimed to investigate the citation patterns of applied linguistics research over two decades as well as the complexity that underpins their making.
The dataset consists of 302 Quartile-1 journal papers that rank in the top 1% by citations in applied linguistics literature (2000-2022), with their detailed bibliometric information collected from Scopus (as of March 2023). Building upon literature, we considered a total of eleven extrinsic factors independent of scientific quality but could potentially affect citation counts, covering journal-related, author-related, and article-related features, respectively. Descriptive analysis was applied to unfold the citation landscape of targeted papers over time characterized by each factor. After a primary look at the bivariate relationship between variables through correlation analysis, multiple linear regression models were adopted to simultaneously examine the extent to which predictor variables are associated with citation outcomes.
The results showed that in the best regression model, time-normalized citations were significantly predicted by six factors: journal prestige, accessibility, co-authorship, research performance, title, and subfield of applied linguistics. The remaining five factors did not exhibit any statistical significance, including internationality, geographical origin, funding, references, and methodology. Certain underlying social mechanisms were further unraveled, among which visibility explains the roles of significant factors in a unified manner, accelerating the recognition and dissemination of research discoveries in the dedicated field. The explanatory strength of all predictors together was observed to be limited (R²=.208, p<.05), but it was expected, considering that they are extrinsic properties unrelated to scientific merit. There is no doubt that the major citation driver should be the intrinsic quality of research, and the remaining variance can be also explained by many other extrinsic features yet to be explored.
To the best of our knowledge, this is the first study that investigates a host of factors contributing to high citations in applied linguistics research. Implications of the research were also discussed, addressing the needs of both applied linguistics researchers and policymakers. We further suggested a more comprehensive approach for evaluative bibliometrics, integrating both qualitative and quantitative indicators to shed light on the whole rewarding system for only good research practices.