Why are some articles highly cited in applied linguistics? A bibliometric study

Abstract

Abstract This study investigated factors influencing the citations of highly cited applied linguistics research over two decades. With a pool of 302 of the top 1% most cited articles in the field, we identified 11 extrinsic factors that were independent of scientific merit but could significantly predict citation counts, including journal-related, author-related, and article-related features. Specifically, the results of multiple linear regression models showed that the time-normalized article citations were significantly predicted by the number of authors, subfield, methodology, title length, CiteScore, accessibility, and scholar h -index. The remaining factors did not exhibit any statistical significance, including the number of references, funding, internationality, and geographical origin. The combined predictive power of all these factors ( R² =.208, p <.05) verifies the role of nonscientific factors contributing to high citations for applied linguistics research. These results encourage applied linguistics researchers and practitioners to recognize the underlying forces affecting research impact and highlight the need for a reward system that exclusively favors sound academic practices.

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No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 13 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.