Evidence map›Paper›PMID 42787329›Full record

ArticleEPJ data science2026

When transparency falls short: auditing platform moderation during a high-stakes election.

Benedetta Tessa, Gautam Kishore Shahi, Amaury Trujillo, Stefano Cresci

Abstract read
In one paragraph

Article in EPJ data science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Benedetta TessaDepartment of Computer Science, University of Pisa, Pisa, Italy.ORCID 0009-0007-6628-4850
Gautam Kishore ShahiUniversity of Duisburg-Essen, Duisburg, Germany.ORCID 0000-0001-6168-0132
Amaury TrujilloIIT-CNR, Pisa, Italy.ORCID 0000-0001-6227-0944
Stefano CresciIIT-CNR, Pisa, Italy.ORCID 0000-0003-0170-2445

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During major political events, social media platforms encounter increased systemic risks. However, it is still unclear if and how they adjust their moderation practices in response. The Digital Services Act Transparency Database provides-for the first time-an opportunity to systematically examine content moderation at scale, allowing researchers and policymakers to evaluate platforms' compliance and effectiveness, especially at high-stakes times. Here we analyze 1.58 billion self-reported moderation actions by the eight largest social media platforms in Europe over an eight-month period surrounding the 2024 European Parliament elections. We found that platforms did not exhibit meaningful signs of adaptation in moderation strategies as their self-reported enforcement patterns did not change significantly around the elections. This raises questions about whether platforms made any concrete adjustments, or whether the structure of the database may have masked them. On top of that, we reveal that initial concerns regarding platforms' transparency and accountability still persist one year after the launch of the Transparency Database. Our findings highlight the limits of current co-regulatory and self-regulatory approaches, and point to the need for stronger enforcement and better data access mechanisms to ensure that online platforms meet their responsibilities in protecting the democratic processes.

Indexed as

2024 European Parliament electionContent moderationData visualizationDigital Service ActOnline regulationSocial mediaStatement of reasons

Identifiers

PMID42787329
PMCPMC13601091

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.