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The use of citation context to detect the evolution of research topics: a large‑scale analysis
| dc.contributor.author | Jebari, Chaker | |
| dc.contributor.author | Herrera Viema, Enrique | |
| dc.contributor.author | Cobo Martín, Manuel Jesús | |
| dc.date.accessioned | 2026-01-09T11:27:52Z | |
| dc.date.available | 2026-01-09T11:27:52Z | |
| dc.date.issued | 2021-02-05 | |
| dc.identifier.citation | Jebari, C; Herrera-Viedma, E; Cobo, MJ. The use of citation context to detect the evolution of research topics: a large‑scale analysis. Scientometrics, 126, 2971-2989. https://doi.org/10.1007/s11192-020-03858-y | es_ES |
| dc.identifier.uri | https://hdl.handle.net/10481/109398 | |
| dc.description | This work has been supported by the Spanish Ministry of Science and Innovation under Grants PID2019-105381GA-I00 (iScience) and PID2019-103880RB-I00. | es_ES |
| dc.description.abstract | With the exponential increase in the number of published papers, discovering how topics evolve becomes increasingly important for anybody involved in research, including researchers, institutes, research funding bodies, and decision-makers. This study proposes a large-scale analysis of the evolution of biomedical and life sciences using the citation contexts of the collected papers, or more precisely their citing sentences. Using 64,350 papers published in PubMed Central between 2008 and 2018, we determined the research trends for ten research topics. Moreover, we studied how these topics evolve across countries and across the most common journals in biomedical and life sciences. | es_ES |
| dc.description.sponsorship | Spanish Ministry of Science and Innovation PID2019-105381GA-I00 (iScience), PID2019-103880RB-I00 | es_ES |
| dc.language.iso | eng | es_ES |
| dc.publisher | Springer Nature | es_ES |
| dc.subject | Citation context | es_ES |
| dc.subject | Research trends | es_ES |
| dc.subject | Topic modeling | es_ES |
| dc.subject | Biomedical and life sciences | es_ES |
| dc.title | The use of citation context to detect the evolution of research topics: a large‑scale analysis | es_ES |
| dc.type | journal article | es_ES |
| dc.rights.accessRights | open access | es_ES |
| dc.identifier.doi | 10.1007/s11192-020-03858-y | |
| dc.type.hasVersion | VoR | es_ES |