U.S. 2020 Facebook and Instagram Election Study

The U.S. 2020 Facebook and Instagram Election Study (US 2020 FIES) is a partnership between Meta and academic researchers to understand the impact of Facebook and Instagram on key political attitudes and behaviors during the US 2020 election. Externally, the project is led by academic collaborators Professors Talia Stroud and Joshua A. Tucker. Professors Tucker and Stroud selected 15 additional researchers to collaborate on this effort, based on their expertise. As results are published in peer-reviewed journals, Meta will make the replication datasets available to qualified academic researchers until June 30, 2031 to reproduce or extend the analyses. The release of datasets will be staggered, as not all papers will be published at the same time. Datasets for studies currently published are available here.

Read the announcement: Data from U.S. 2020 Presidential Election Facebook and Instagram Study Now Available at ICPSR

Cite this project: U.S. 2020 Facebook and Instagram Election Study. Inter-university Consortium for Political and Social Research [distributor]. https://socialmediaarchive.org/collection/US2020

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U.S. 2020 Facebook and Instagram Election Study 22 records found 1 - 10nextSearch took 0.17 seconds. 
1.
This table includes platform data for Instagram participants in the Deactivation experiment. Each row of the dataset corresponds to data from a participant’s Instagram [...]
23 August 2024 | Dataset |
2.
This table includes platform data for Facebook participants in the Deactivation experiment. Each row of the dataset corresponds to data from a participant’s Facebook user [...]
23 August 2024 | Dataset |
3.
This record is for replication code for datasets in the U.S. 2020 Facebook and Instagram Election Study. Code will be provided along with related datasets in a secure vir [...]
27 July 2023 | Dataset |
4.
Researchers at New York University, the University of Texas at Austin, and other academic institutions, as well as Meta, partnered with NORC at the University of Chicago [...]
27 July 2023 | Dataset |
5.
The metrics in this dataset measure participants' views of posts with links to civic news domains over the study period. The dataset contains domain-level metrics from Fa [...]
27 July 2023 | Dataset |
6.
This dataset measures the ideological segregation index and favorability score of the potential, exposed and engaged audience of posts with links to domains and URLs clas [...]
27 July 2023 | Dataset |
7.
This dataset measures the ideological segregation index and favorability score of the potential, exposed and engaged audience of posts with links to domains and URLs clas [...]
27 July 2023 | Dataset |
8.
The metrics in this dataset measure the audience size and views of posts with links to a specific pair of URLs classified as civic news. The dataset contains URL-level me [...]
27 July 2023 | Dataset |
9.
The metrics in this dataset measure the audience size and views of posts with links to a specific pair of domains classified as civic news. The dataset contains domain-le [...]
27 July 2023 | Dataset |
10.
The metrics in this dataset measure users who potentially viewed posts with links to civic news URLs that were shared by one of their connections. The dataset contains UR [...]
27 July 2023 | Dataset |

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