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Purpose The purpose of this study is to evaluate the context and background of citations received by the top 100 highly cited articles published in the top five Emerald journals from 2014 to 2023. Furthermore, it proposes a novel method for tracing scholarly influence through contextual smart citation analysis using Scite. Design/methodology/approach This study used bibliometric techniques, as the entire analysis was based on the bibliographical records of publications. The top five journals published by Emerald were identified based on CiteScore, and the top 100 highly cited articles were selected. Later, the citing documents associated with the top 100 articles were extracted from Scite, an emerging platform that uses artificial intelligence (AI) and natural language processing (NLP) to provide a comprehensive understanding of citations. Collected data were processed and analyzed using MS Excel, Google Sheets, and Tableau. Findings The study found that most of the citing documents were published by Emerald and the journal Supply Chain Management: An International Journal was the leading journal where the highest number of citing documents were published. A total of 5,995 citations were concentrated in the “Introduction/Conceptual framework/Theoretical background” sections followed by “Literature review” (2,224), “Method/Tools/Techniques” (988), “Analysis/Result/Discussion” (2,478) and “Conclusion/Future Research Direction” (269) sections. The study also found that the most numbers of citations were “mentioning cites”. Originality/value The study explored the context and background of citations to scholarly articles using Scite and introduced Scite as an innovative tool in citation analysis, providing a promising avenue for future research in assessing academic impacts.
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Stored only when both papers are in the corpus — 5 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.