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Data

Media Corruption Score

V-Dem
See all data and research on:
Democracy

What you should know about this indicator

We provide two kinds of regional averages: country averages and population-weighted averages. Country averages weigh each country equally and give a sense of how the typical country is doing. Population-weighted averages weigh countries with larger populations more and therefore better reflect the average person's experience.

How is this data described by its producer - V-Dem?

Question: Do journalists, publishers, or broadcasters accept payments in exchange for altering news coverage?

Responses:

  • 0: The media are so closely directed by the government that any such payments would be either unnecessary to ensure pro-government coverage or ineffective in producing anti-government coverage.
  • 1: Journalists, publishers, and broadcasters routinely alter news coverage in exchange for payments.
  • 2: It is common, but not routine, for journalists, publishers, and broadcasters to alter news coverage in exchange for payments.
  • 3: It is not normal for journalists, publishers, and broadcasters to alter news coverage in exchange for payments, but it happens occasionally, without anyone being punished.
  • 4: Journalists, publishers, and broadcasters rarely alter news coverage in exchange for payments, and if it becomes known, someone is punished for it.

Scale: Ordinal, converted to interval by the measurement model.

V-Dem indicator name: v2mecorrpt

Media Corruption Score
V-Dem
Gauges the frequency with which journalists, publishers, or broadcasters accept payments to modify news content, indicating the integrity (or corruption) of the media sphere.
Source
V-Dem (2026) – processed by Our World in Data
Last updated
March 17, 2026
Next expected update
March 2027
Date range
1900–2025

Sources and processing

This data is based on the following sources

V-Dem – Democracy report

The Varieties of Democracy (V-Dem) project publishes data and research on democracy and human rights.

It acknowledges that democracy can be characterized differently and measures electoral, liberal, participatory, deliberative, and egalitarian characterizations of democracy.

The project relies on evaluations by around 3,500 country experts and supplementary work by its researchers to assess political institutions and the protection of rights.

The project is managed by the V-Dem Institute, based at the University of Gothenburg in Sweden.

This snapshot contains all 531 V-Dem indicators and 251 indices + 62 other indicators from other data sources.

For more information, please refer to https://www.v-dem.net/data/the-v-dem-dataset/

Retrieved on
March 17, 2026
Retrieved from
https://v-dem.net/data/the-v-dem-dataset/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Coppedge, Michael, John Gerring, Carl Henrik Knutsen, Staffan I. Lindberg, Jan Teorell, David Altman, Fabio Angiolillo, Michael Bernhard, Agnes Cornell, M. Steven Fish, Linnea Fox, Lisa Gastaldi, Haakon Gjerløw, Adam Glynn, Ana Good God, Sandra Grahn, Allen Hicken, Katrin Kinzelbach, Joshua Krusell, Kyle L. Marquardt, Kelly McMann, Valeriya Mechkova, Juraj Medzihorsky, Natalia Natsika, Anja Neundorf, Pamela Paxton, Daniel Pemstein, Johannes von Römer, Brigitte Seim, Rachel Sigman, Svend-Erik Skaaning, Jeffrey Staton, Aksel Sundström, Marcus Tannenberg, Eitan Tzelgov, Yi-ting Wang, Felix Wiebrecht, Tore Wig, Steven Wilson and Daniel Ziblatt. 2026. "V-Dem [Country-Year/Country-Date] Dataset v16" Varieties of Democracy (V-Dem) Project. https://doi.org/10.23696/vdemds26
Pemstein, Daniel, Kyle L. Marquardt, Eitan Tzelgov, Yi-ting Wang, Juraj Medzihorsky, Joshua Krusell, Farhad Miri, and Johannes von Römer. 2026. "The V-Dem Measurement Model: Latent Variable Analysis for Cross-National and Cross-Temporal Expert-Coded Data". V-Dem Working Paper No. 21. 11th edition. University of Gothenburg: Varieties of Democracy Institute.

The Varieties of Democracy (V-Dem) project publishes data and research on democracy and human rights.

It acknowledges that democracy can be characterized differently and measures electoral, liberal, participatory, deliberative, and egalitarian characterizations of democracy.

The project relies on evaluations by around 3,500 country experts and supplementary work by its researchers to assess political institutions and the protection of rights.

The project is managed by the V-Dem Institute, based at the University of Gothenburg in Sweden.

This snapshot contains all 531 V-Dem indicators and 251 indices + 62 other indicators from other data sources.

For more information, please refer to https://www.v-dem.net/data/the-v-dem-dataset/

Retrieved on
March 17, 2026
Retrieved from
https://v-dem.net/data/the-v-dem-dataset/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Coppedge, Michael, John Gerring, Carl Henrik Knutsen, Staffan I. Lindberg, Jan Teorell, David Altman, Fabio Angiolillo, Michael Bernhard, Agnes Cornell, M. Steven Fish, Linnea Fox, Lisa Gastaldi, Haakon Gjerløw, Adam Glynn, Ana Good God, Sandra Grahn, Allen Hicken, Katrin Kinzelbach, Joshua Krusell, Kyle L. Marquardt, Kelly McMann, Valeriya Mechkova, Juraj Medzihorsky, Natalia Natsika, Anja Neundorf, Pamela Paxton, Daniel Pemstein, Johannes von Römer, Brigitte Seim, Rachel Sigman, Svend-Erik Skaaning, Jeffrey Staton, Aksel Sundström, Marcus Tannenberg, Eitan Tzelgov, Yi-ting Wang, Felix Wiebrecht, Tore Wig, Steven Wilson and Daniel Ziblatt. 2026. "V-Dem [Country-Year/Country-Date] Dataset v16" Varieties of Democracy (V-Dem) Project. https://doi.org/10.23696/vdemds26
Pemstein, Daniel, Kyle L. Marquardt, Eitan Tzelgov, Yi-ting Wang, Juraj Medzihorsky, Joshua Krusell, Farhad Miri, and Johannes von Römer. 2026. "The V-Dem Measurement Model: Latent Variable Analysis for Cross-National and Cross-Temporal Expert-Coded Data". V-Dem Working Paper No. 21. 11th edition. University of Gothenburg: Varieties of Democracy Institute.

How we process data at Our World in Data

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At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

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Notes on our processing step for this indicator

Region aggregates

The default regional aggregates have been estimated by averaging the country values. These are only estimated since 1900 and when data for most countries and populations is available (i.e. 70% for most continents). We have used the list of countries in 1900 as a reference.

In addition, regional aggregates with names like "Region (population-weighted)" have been estimated by averaging the country values weighted by population. The population values are from the UN WPP 2024 revision dataset. These are only estimated when 70% of people in region have data for the given year.

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  • All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
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Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Media Corruption Score”, part of the following publication: Bastian Herre, Lucas Rodés-Guirao, and Esteban Ortiz-Ospina (2013) - “Democracy”. Data adapted from V-Dem. Retrieved from https://archive.ourworldindata.org/20260318-112846/grapher/media-corruption-score.html [online resource] (archived on March 18, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

V-Dem (2026) – processed by Our World in Data

Full citation

V-Dem (2026) – processed by Our World in Data. “Media Corruption Score – V-Dem” [dataset]. V-Dem, “Democracy report v16” [original data]. Retrieved April 1, 2026 from https://archive.ourworldindata.org/20260318-112846/grapher/media-corruption-score.html (archived on March 18, 2026).

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Data API

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Data URL (CSV format)
https://ourworldindata.org/grapher/media-corruption-score.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/media-corruption-score.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/media-corruption-score.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/media-corruption-score.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/media-corruption-score.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/media-corruption-score.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/media-corruption-score.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/media-corruption-score.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear