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Beyond traditional metrics: Assessing OpenAlex and Scopus for SSH research evaluation

Tindaro Cicero & Scipione Sarlo

Journal of Information Science2026https://doi.org/10.1177/01655515251411204article
AJG 2
Weight
0.50

What the paper says

Recent debates on research evaluation in the Social Sciences and Humanities (SSH) have underscored the limitations of traditional bibliometric databases – such as Scopus and Web of Science – in capturing the linguistic and regional diversity characteristic of these fields. This study presents the first large-scale comparison between OpenAlex and Scopus, based on the journal classification system of Italy’s National Agency for the Evaluation of Universities and Research Institutes (ANVUR). Using a data set of 23,304 classified journals, we compare the two databases in terms of coverage, language diversity, journal quality, and overlap. Our results show that OpenAlex indexes a substantially higher proportion of journals (66.9% vs 48.2%), includes more top-tier journals (81.9% vs 68.5%), and offers broader language inclusivity – particularly for French, Spanish, and German publications. However, unlike Scopus, OpenAlex does not apply editorial quality control mechanisms. We conclude by discussing the trade-offs between coverage and selectivity, and offer practical implications for the use of bibliometric data in SSH research assessment.

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https://doi.org/https://doi.org/10.1177/01655515251411204

Or copy a formatted citation

@article{tindaro2026,
  title        = {{Beyond traditional metrics: Assessing OpenAlex and Scopus for SSH research evaluation}},
  author       = {Tindaro Cicero & Scipione Sarlo},
  journal      = {Journal of Information Science},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/01655515251411204},
}

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Beyond traditional metrics: Assessing OpenAlex and Scopus for SSH research evaluation

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.