Evidence map›Paper›PMID 38627434›Full record

ArticleScientific reports2024

First public dataset to study 2023 Turkish general election.

Ali Najafi, Nihat Mugurtay, Yasser Zouzou, Ege Demirci, Serhat Demirkiran, Huseyin Alper Karadeniz, Onur Varol

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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

7 authors.

Ali Najafi *Faculty of Engineering and Natural Sciences, Sabanci University, 34456, Istanbul, Turkey.
Nihat Mugurtay *Faculty of Engineering and Natural Sciences, Sabanci University, 34456, Istanbul, Turkey.
Yasser Zouzou *Faculty of Engineering and Natural Sciences, Sabanci University, 34456, Istanbul, Turkey.
Ege DemirciFaculty of Engineering and Natural Sciences, Sabanci University, 34456, Istanbul, Turkey.
Serhat DemirkiranFaculty of Engineering and Natural Sciences, Sabanci University, 34456, Istanbul, Turkey.
Huseyin Alper KaradenizFaculty of Engineering and Natural Sciences, Sabanci University, 34456, Istanbul, Turkey.
Onur VarolFaculty of Engineering and Natural Sciences, Sabanci University, 34456, Istanbul, Turkey. onur.varol@sabanciuniv.edu.

Funding

Türkiye Bilimsel ve Teknolojik Araştırma Kurumu 121C220
6 · The paper itself

Abstract

In the context of Turkiye's most recent parliamentary and presidential elections ("seçim" in Turkish), social media has played an important role in shaping public debate. It is of utmost importance to capture social media trends during the 2023 Turkish elections, since it uncovers a great deal of information of election propaganda, political debates, smear campaigns, and election manipulation by domestic and international actors. We provide a comprehensive dataset for social media researchers to study Turkish elections, develop tools to prevent online manipulation, and gather novel information to inform the public. We are committed to continually improving the data collection and updating it regularly leading up to the election. Using the #Secim2023 dataset, researchers can examine the social and communication networks between political actors, track current trends, and investigate emerging threats to election integrity. Our dataset and analysis code available through Harvard Dataverse and Github, respectively.

Identifiers

PMID38627434
PMCPMC11021468

What OpenQuestion holds

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Registered trials

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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.