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Data

Interpersonal trust in the United States

About this data

Source
NORC at the University of Chicago (2021) – processed by Our World in Data
Last updated
March 7, 2022
Date range
1972–2018
Unit
%

Sources and processing

This data is based on the following sources

NORC at the University of Chicago – General Social Survey

The General Social Survey (GSS) is a project of the independent research organization NORC at the University of Chicago, with principal funding from the National Science Foundation.

Extracted from the GSS Data Explorer Variable "trust" (https://gssdataexplorer.norc.org/variables/441/vshow) -> Tabulate Column: Trust (Can people be trusted) Row: Year (GSS year for this respondent) Weight var: WTSSCOMP Sample design: Simple Random Sample Exclude missing: Yes Note: as of 7 Mar 2022 there is a typo in the values on the GSS website - we think that "Can't trust" actually mean "Can trust" and is the positive response, while "Can't be too careful" is the negative response.

Retrieved on
March 7, 2022
Retrieved from
https://gssdataexplorer.norc.org/variables/441/vshow
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.
Davern, Michael; Bautista, Rene; Freese, Jeremy; Morgan, Stephen L.; and Tom W. Smith. General Social Surveys, 1972-2021 Cross-section [machine-readable data file, 68,846 cases]. Principal Investigator, Michael Davern; Co-Principal Investigators, Rene Bautista, Jeremy Freese, Stephen L. Morgan, and Tom W. Smith; Sponsored by National Science Foundation. – NORC ed. – Chicago: NORC, 2021: NORC at the University of Chicago [producer and distributor]. Data accessed from the GSS Data Explorer website at gssdataexplorer.norc.org.

The General Social Survey (GSS) is a project of the independent research organization NORC at the University of Chicago, with principal funding from the National Science Foundation.

Extracted from the GSS Data Explorer Variable "trust" (https://gssdataexplorer.norc.org/variables/441/vshow) -> Tabulate Column: Trust (Can people be trusted) Row: Year (GSS year for this respondent) Weight var: WTSSCOMP Sample design: Simple Random Sample Exclude missing: Yes Note: as of 7 Mar 2022 there is a typo in the values on the GSS website - we think that "Can't trust" actually mean "Can trust" and is the positive response, while "Can't be too careful" is the negative response.

Retrieved on
March 7, 2022
Retrieved from
https://gssdataexplorer.norc.org/variables/441/vshow
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.
Davern, Michael; Bautista, Rene; Freese, Jeremy; Morgan, Stephen L.; and Tom W. Smith. General Social Surveys, 1972-2021 Cross-section [machine-readable data file, 68,846 cases]. Principal Investigator, Michael Davern; Co-Principal Investigators, Rene Bautista, Jeremy Freese, Stephen L. Morgan, and Tom W. Smith; Sponsored by National Science Foundation. – NORC ed. – Chicago: NORC, 2021: NORC at the University of Chicago [producer and distributor]. Data accessed from the GSS Data Explorer website at gssdataexplorer.norc.org.

How we process data at Our World in Data

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

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.

Read about our data pipeline

Reuse this work

  • 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.
  • All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

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: Interpersonal trust in the United States”. Our World in Data (2026). Data adapted from NORC at the University of Chicago. Retrieved from https://archive.ourworldindata.org/20260511-092124/grapher/interpersonal-trust-in-the-us.html [online resource] (archived on May 11, 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:

NORC at the University of Chicago (2021) – processed by Our World in Data

Full citation

NORC at the University of Chicago (2021) – processed by Our World in Data. “Interpersonal trust in the United States” [dataset]. NORC at the University of Chicago, “General Social Survey” [original data]. Retrieved May 13, 2026 from https://archive.ourworldindata.org/20260511-092124/grapher/interpersonal-trust-in-the-us.html (archived on May 11, 2026).

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Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://ourworldindata.org/grapher/interpersonal-trust-in-the-us.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/interpersonal-trust-in-the-us.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/interpersonal-trust-in-the-us.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/interpersonal-trust-in-the-us.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/interpersonal-trust-in-the-us.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

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

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