SciVal Metric: Outputs in Top Citation Percentiles

• Benchmark the contributions towards the most influential, highly cited publications in the world of entities of different sizes, but in similar disciplines
• It is advised to select the “Percentage” option when comparing entities of different sizes, to normalize for this variable
• Distinguish between entities whose performance seems similar when viewed by other metrics, such as Scholarly Output, Citations per Publication, or Collaboration
• Showcase the performance of a prestigious entity whose publications are amongst the most cited and highly visible publications of the scholarly world
• Present citation data in a way that inherently considers the lower number of citations received by relatively recent publications, thus avoiding the dip in recent years seen with Citation Count and Citations per Publication

• Comparing entities in different disciplines:

  • Citation counts tend to be higher in disciplines such as immunology and microbiology, whose academics tend to publish frequently and include long reference lists, than in mathematics, where publishing 1 item every 5 years that refers to 1 or 2 other publications is common; these differences reflect the distinct behavior of researchers in distinct subject fields, and not differences in performance.
  • It is not advisable to use this metric to compare entities in distinct disciplines without accounting for these differences.
  • When comparing entities made up of a mixture of disciplines, such as an Institution or Country, it is advised to apply the Research Area filter to focus on one field that is common between all the entities.
• Entities are small and there may be gaps in their output within the Scopus coverage. A single missing highly cited publication from a small data set will have a significant negative impact on apparent performance. Although it is relatively unlikely that such prominent publications are not indexed by Scopus, we advise users to be vigilant and to bear this possible limitation in mind.
• There is a concern that excessive self-citations may be artificially inflating the number of publications that appear in the top percentiles. Users can judge whether the level of self-citations is higher than expected by deselecting the “Include self-citations” option.
• Understanding the status of publications of an early-career researcher, or those resulting from the first stages of a new strategy, where insufficient time may have passed to ensure that presence in top citation percentiles is a reliable indicator of performance. These situations can be addressed by metrics that are useful immediately upon publication, such as Publications in Top Journal Percentiles.
• Trust needs to be built in the metrics in SciVal. The citation thresholds may depend on the entire Scopus database, and it will be difficult for a user to validate these boundaries. Users are advised to select simpler metrics, such as Citations per Publication, if trust in the accuracy of the SciVal calculations needs to be built.

• Cited Publicationsopens in new tab/window, which indicates the reliability with which an entity’s output is built on by subsequent research by counting publications that have received at least 1 citation. It is not affected by 1 or a few very highly cited publications.
• Publications in Top Journal Percentilesopens in new tab/window, which indicates the extent to which an entity’s publications are present in the most-cited journals in the data universe, and is independent of the citations received by the publications themselves. This is a logical partner metric.
• The set of all other “Power Metrics” whose value tends to increase as the entity becomes bigger: Scholarly Output, Subject Area Count, Scopus Source Title Count, Citation Count, Cited Publications (“Total value”), Number of Citing Countries, Collaboration (“Total value”), Academic-Corporate Collaboration (“Total value”), Publications in Top Journal Percentiles (“Total value”), and h-indices
• The set of “time-independent metrics”, which provide useful, reliable information immediately upon publication and do not rely on the passing of time for useful data to accumulate: Scholarly Output, Subject Area Count, Scopus Source Title Count, Collaboration, Academic-Corporate Collaboration, and Publications in Top Journal Percentiles

Scenario: The user would like to calculate the Outputs in the Top Citation Percentiles of an entity that consists of 6 publications, and has selected a number of viewing and calculation options.

Click here (Opens in a new tab or window)opens in new tab/windowto see a PDF example of the Outputs in the Top Citation Percentiles calculation.

We no longer offer self-citation exclusion for this metric. Self-citation exclusion applies to the entity being analyzed, but cannot be applied to the whole data universe in SciVal as the entity there is the individual publication. Therefore, the thresholds used for each percentile do not change with self-citation exclusion, but the analyzed entity data does, creating an inconsistency that limits the insights that the metric option provides.