Evidence map›Paper›PMID 38979081›Full record

ArticlePNAS nexus2024

Systematic discrepancies in the delivery of political ads on Facebook and Instagram.

Dominik Bär, Francesco Pierri, Gianmarco De Francisci Morales, Stefan Feuerriegel

Abstract read
In one paragraph

Article in PNAS nexus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
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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.

Dominik BärLMU Munich, Munich 80539, Germany.ORCID https://orcid.org/0000-0002-3251-4167
Francesco PierriDipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan 20133, Italy.ORCID https://orcid.org/0000-0002-9339-7566
Gianmarco De Francisci MoralesCENTAI, Turin 10138, Italy.ORCID https://orcid.org/0000-0002-2415-494X
Stefan FeuerriegelLMU Munich, Munich 80539, Germany.ORCID https://orcid.org/0000-0001-7856-8729

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Political advertising on social media has become a central element in election campaigns. However, granular information about political advertising on social media was previously unavailable, thus raising concerns regarding fairness, accountability, and transparency in the electoral process. In this article, we analyze targeted political advertising on social media via a unique, large-scale dataset of over 80,000 political ads from Meta during the 2021 German federal election, with more than

Indexed as

algorithmic discrepancieselection campaignspoliticssocial mediatargeted advertising

Identifiers

PMID38979081
PMCPMC11229815

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

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.