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Data, analytic code, and findings based on a large-scale survey conducted by Ipsos Public Affairs for BuzzFeed News.
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README.md

Fake News Survey Data and Analysis

This repository contains data, analytic code, and findings based on a large-scale survey conducted by Ipsos Public Affairs for BuzzFeed News.

The findings support the BuzzFeed News article, "Most Americans Who See Fake News Believe It, New Survey Says," published December 6, 2016. That article also contains additional details about the survey design and context.

Data

  • General cross-tabs, compiled by Ipsos, and a data dictionary describing the variables, can be found here.

  • The raw survey response data, courtesy of Ipsos, can be found here, as both CSV and SPSS files.

  • BuzzFeed News has also created a simplified CSV containing the following main columns for each headline presented to each respondent:

    • Respondent ID
    • Headline ID (A-K)
    • Whether this headline is one of the five fake-news headlines
    • Order in which the respondent saw the headline (1-6)
    • Whether the respondent recalled having seen or heard about the headline (yes/no/unsure)
    • Whether the respondent believed the headline to be accurate (very accurate/somewhat accurate/not very accurate/not at all accurate)
    • The respondent's survey weight, as determined by Ipsos

Analysis

A notebook containing the calculations can be found here. It's written in Python, but the resulting tables should still be generally legible to non-prgrammers.

Feedback / Questions?

Contact Jeremy Singer-Vine at jeremy.singer-vine@buzzfeed.com.

Looking for more from BuzzFeed News? Click here for a list of our open-sourced projects, data, and code.

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