The Dissent Score Data Set

The dissent score data set provides a standardized, public, ready-to-use data set with a measure of dissent at the country-year level Rainey, Roe, Wang, and Dietrich’s “The Dissent Score: Using Events Data to Measure Dissent.” On this webpage, we supply the preprint describing the data, the data sets, and a careful description of how we wrangled the IDEA data into our dissent score.

Get the Data

The dissent score data set is permanently archived on Dataverse. You can download the data directly from Dataverse with the code below.

# load packages
library(tidyverse)
library(dataverse)

# get the dissent score data set from dataverse
dissent <- get_dataframe_by_name(
  filename = "dissent-scores.tab",
  dataset  = "doi:10.7910/DVN/CL4CA8",
  server   = "dataverse.harvard.edu", 
  original = TRUE, 
  .f = readr::read_csv) |> 
  glimpse()

Rows: 2,775
Columns: 15
$ release             <chr> "V0.1 (Preprint)", "V0.1 (Preprint)", "V0.1 (Prepr…
$ release_date        <date> 2023-12-18, 2023-12-18, 2023-12-18, 2023-12-18, 2…
$ data_source         <chr> "IDEA", "IDEA", "IDEA", "IDEA", "IDEA", "IDEA", "I…
$ created_date        <date> 2023-12-18, 2023-12-18, 2023-12-18, 2023-12-18, 2…
$ country_name        <chr> "United States", "United States", "United States",…
$ ccode               <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 20, 2…
$ stateabb            <chr> "USA", "USA", "USA", "USA", "USA", "USA", "USA", "…
$ year                <dbl> 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 19…
$ n_events            <dbl> 135537, 140735, 151180, 177717, 194368, 195981, 20…
$ n_dissent_events    <dbl> 118, 109, 124, 138, 127, 117, 123, 130, 147, 121, …
$ frac_dissent_events <dbl> 0.0008706110, 0.0007745053, 0.0008202143, 0.000776…
$ avg_pi              <dbl> 0.0008690543, 0.0007750752, 0.0008211722, 0.000779…
$ avg_eta             <dbl> -7.051493, -7.166315, -7.107983, -7.160229, -7.331…
$ dissent_score       <dbl> -0.62807636, -0.67911036, -0.65318394, -0.67640508…
$ se_dissent_score    <dbl> 0.04107096, 0.04241524, 0.03997557, 0.03736980, 0.…

Cite the Data

Paper

Rainey, Carlisle, Harley Roe, Qing Wang, and Nick Dietrich. 2023. “The Dissent Score: Using Events Data to Measure Dissent.” https://osf.io/preprints/socarxiv/dw7np.

Data Set

Rainey, Carlisle, Harley Roe, Qing Wang, and Nick Dietrich. 2023. “Dissent Scores.” https://doi.org/10.7910/DVN/CL4CA8. Harvard Dataverse.

Understand the Data

To create the dissent score, we follow the standard practice in the literature and use the number of dissent events reported in events data sets. However, we make two improvements.

First, we adjust for variation in media scrutiny by using the rate of dissent events—the number of dissent events compared to the total number of events reported in the data set.
Second, we use a hierarchical model to partially pool these rates within and across countries to reduce the error in places with few events.

For more details, see the paper.

Improve the Data

We offer both data set and a method. Both can be improved and/or extended! We welcome bug reports, tiny suggestions, and big criticisms. We hope that others will find this useful and help us make it better.