2020/01/31 by Xiomara S. Q. Chacón, Xiomara Sulvey Quispe Chacon, Thiago Christiano Silva +2
Computer Science · Decision Sciences · Mathematics · Psychology · #Computer science #Factor (programming language) #Geography #Impact factor #Linguistics #Mathematics #Meteorology #Political science #Prestige #Psychology #Research Data Management Practices #Visibility #Visibility graph #cs.DL #scientometrics and bibliometrics research
paper · pdf · doi:10.1007/s11192-020-03651-x
published as Scientometrics 125, 625-639 (2020) · Scientometrics, 2020
openalex publication_date 2020/08/05 · arxiv created 2020/08/06 · arxiv updated 2020/10/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
The impact factor has been extensively used in the last years to assess journals visibility and prestige. While the impact factor is useful to compare journals, the specificities of subfields visibility in journals are overlooked whenever visibility is measured only at the journal level. In this paper, we analyze the subfields visibility in a subset of over 450,000 Physics papers. We show that the visibility of subfields is not regular in the considered dataset. In particular years, the variability in subfields impact factor in a journal reached 75% of the average subfields impact factor. We also found that the difference of subfields visibility in the same journal can be even higher than the difference of visibility between different journals. Our results show that subfields impact is an important factor accounting for journals visibility.