By Dr

Giulia Stefenelli, Scientific Communications Lead, MDPI and Dr Enric Sayas, Business Analyst, MDPI– Silver Sponsor at University

Press REDUX Conference 2025

 

 

 

 

 

 

The context of self-citation scrutiny

 

 

Self-citations are a key topic in

academic publishing. While self-citations can naturally reflect a journal’s

specialization and research depth, concerns arise when they artificially

inflate metrics like the Impact Factor (IF) and CiteScore, potentially

distorting a journal’s perceived value.

 

 

 

 

 

This topic garnered significant attention

following the release of Clarivate’s 2024 Journal Citation Report (JCR), which included

the suppression of 17 journals from a range of publishers for excessive

self-citation patterns (see, Clarivate

Suppression List 2023).

This prompted MDPI to analyze the citation patterns of its 237 JCR-indexed

journals, ensuring alignment with industry norms and reinforcing our commitment

to transparency, improvement, and integrity.

 

 

 

 

Methodology

 

 

As part of this assessment, we

compared MDPI journals to others found in the same JCR category. Using data

from Web of Science (WoS), which aligns with the data impacting JCR scores and is

independently accessible, enabled an accurate and open comparison with other

publishers’ datasets.

 

 

 

 

 

The

original data and python scripts used can be found here: 10.5281/zenodo.14844342

 

 

 

 

Key Findings: Alignment with industry norms

 

 

 

 

Findings

reveal MDPI’s citation practices are sound, consistent, and comparable to

prevailing industry trends and established norms.

 

 

 

 

 

The evaluation includes 237 MDPI

journals indexed in the JCR and analyzed their Impact Factor (IF) both with and

without self-citations for the latest available year, 2024. Self-citations

rates (SCRs) were also examined relative to category averages

and assess how self-citations influence their overall ranking within their

respective categories.

 

 

 

 

 

Findings show some variability in

self-citation. Overall, however, MDPI journals align to industry norms and the

limits established by WoS. MDPI has very few journals with high SCRs in their

category compared to other leading publishers.

 

 

 

In 2024,

MDPI’s average SCR was 14.85%, positioning the publisher 6th among the top ten

publishers by SCR and 4th by publication volume (Figure 1).

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SCRs across MDPI’s journals were calculated

individually and compared to the average rates within their respective JCR

categories. For journals indexed in multiple categories, the first category was

selected.

 

 

 

 

 

 

Beyond Citations: Emphasizing broader research impact

 

 

We also examined the overall

distribution of SCRs across all JCR journals and compared them to MDPI journals.

Figure 2 shows SCRs are not normally distributed but exhibit a right-skewed

distribution. This indicates that while most journals have relatively low SCRs,

some exhibit significantly higher rates.

 

 

 

 

 

 

 

 

 

 

 

 

 

Based on

this distribution, we analysed SCRs using percentile rankings, defining outlier

journals as those exceeding the 95th percentile (top 5%). The median self-citation

rate of all JCR journals was 0.12 while the median for MDPI-only journals was

0.14. This difference was shown to be not significative using a Wilcoxon

rank-sum test (P-value 0.33374); there is no statistically significant

difference in SCRs between MDPI journals and all journals in the dataset. Any

observed difference in medians is due to random variation rather than a true

difference in behaviour.

 

 

 

 

 

A similar

approach can be applied within each JCR category, identifying outliers based

solely on SCRs within their respective categories.

 

 

 

 

 

This was

performed by grouping journals by their primary JCR category and generating SCR

distributions within each. This allows for identifying outliers at the category

level based on SCRs within the same field.

 

 

 

 

 

 

 

Per Figure 3, outlier SCRs vary

widely, from 20% to nearly 100%. For MDPI journals, however, the range is more

contained, between 20% and 40%. Notably, some MDPI journals with relatively

high SCRs are not classified as outliers, suggesting they belong to JCR

categories with inherently high SCRs. This highlights the need for

category-specific assessments rather than a universal threshold.

 

 

 

 

 

Overall, we found that among the top

10 publishers (excluding MDPI), 4.7% of journals were classified as outliers

based on their SCRs, whereas for MDPI, this figure was 2.3%.

 

 

 

 

Minimal impact on Rankings

 

 

We also

examined whether excluding self-citations from the IF calculation significantly

affects journal rankings within their categories. To do this, we ranked all the

journals per category based on their IF both with and without self-citations,

then observed the changes in ranking and quartile distribution. The analysis

revealed that any category

ranking changes were modest, with shifts averaging 7% based on 2024 data.

 

 

 

 

 

Key findings from the 237 MDPI journals

analyzed reveal:

 

• 105 journals (44%) saw a ranking change between 10% and -10%, when self-citations were excluded.
• 74 journals saw a ranking decrease, and 49 journals saw a ranking increase when not counting self-citations.
• Six journals had a ranking decrease higher than 20%, while eight journals had a ranking increase higher than 20%.

 

 

 

The

analysis also looked at whether any MDPI journals experienced changes in

quartile rankings due to self-citations. As Table 2 shows, 14 journals decreased

quartile when self-citations were removed: five journals from Q1 to Q2 and nine

journals from Q2 to Q3. However, we also observed seven journals that increased

their quartile when self-citations were removed: one journal from Q4 to Q3, three

journals from Q3 to Q2, and three journals from Q2 to Q1.  Removing self-citations from MDPI journal IFs

left 91% of journals in their original quartile. While some moved out of Q1,

others moved in, with 97% of MDPI’s indexed portfolio unaffected by these

shifts.

 

 

 

 

 

 

 

 

 

The

results reinforce that self-citations have minimal influence on MDPI journal

rankings, emphasizing the integrity of editorial practices and the absence of

any deliberate efforts to manipulate impact.

 

 

 

 

Reinforcing transparency and integrity

 

 

 

 

As part

of our continued commitment to integrity, transparency and protecting the

scientific record, we welcome further scrutiny of the data used. We believe

research impact goes beyond metrics to advancing knowledge, addressing societal

challenges, and creating meaningful academic conversations. Broader indicators,

such as research quality, societal relevance, and overall scholarly influence

are equally important.

 

 

 

 

 

 

 

We invite our authors, editors, and readers to

explore this analysis further and engage with us in conversations about

responsible publishing. Together, we can continue to uphold the high standards

of scholarly communication.

 

 

 

About MDPI

 

 

Headquartered in Switzerland, MDPI is an Open Access

publisher with a portfolio of more than 440 journals across all scientific

disciplines. To date, MDPI has published the works of over 3.7 million

researchers, collaborating with an extensive network of academic institutions

and scientific societies worldwide. Above all, MDPI is committed to ensuring

that high-quality research is freely accessible to readers across the globe.

 

 

 

 

About the Authors

 

 

 

 

 

Dr. Giulia Stefenelli, Scientific Communications Lead,

 

leverages her expertise in science communication, editorial processes, and Open

Access (OA) promotion to address both institutional and country-specific

challenges. She collaborates with teams across PR, Editorial Procedures,

Institutional Partnerships, Research Integrity, AI and more, developing

strategies to engage stakeholders, including policymakers, academics, and

industry leaders. Her responsibilities include enhancing MDPI’s scientific

network and promoting OA initiatives at events worldwide supporting different

departments efforts, and ensuring effective communication to both specialist

and broader audiences.



Dr. Enric Sayas is a Business Analyst specializing in the integration of AI and Machine Learning in scientific publishing. Within MDPI’s AI team, he combines his editorial expertise with his passion for AI to support the development of AI-driven solutions tailored to editorial needs, enhancing efficiency and decision-making. His interests extend to data science methodologies applied to scientific publishing, as well as the broader impact of AI on open science, peer review, and the future of scientific publishing.

 

 

 

 

 

 

About University Press Redux 2025

 

 

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