000000031 001__ 31
000000031 005__ 20250507133255.0
000000031 02470 $$a10.3886/tt1k-sk28$$2DOI
000000031 037__ $$aADMIN
000000031 245__ $$aExposure to Facebook Posts with Civic News Domains
000000031 251__ $$av1
000000031 269__ $$a2023-07-27
000000031 336__ $$aDataset
000000031 500__ $$aThe 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.
000000031 510__ $$aMeta Platforms, Inc. Exposure to Facebook Posts with Civic News Domains. Inter-university Consortium for Political and Social Research [distributor], 2023-07-27. https://doi.org/10.3886/tt1k-sk28
000000031 520__ $$aThe metrics in this dataset measure users who viewed posts with links to civic news domains. The dataset contains domain-level metrics from Facebook activity data for adult U.S. monthly active users, aggregated over the study period. Includes content views, audience size, content attributes, user attributes.
000000031 536__ $$oMeta Platforms, Inc.
000000031 540__ $$aThis dataset has two levels of access: Public and Virtual Data Enclave.
<ul>
<li>Public files can be downloaded directly from the dataset record. Typically, documentation files such as READMEs and codebooks are made public.</li>

<li>Virtual Data Enclave files have access restrictions due to the sensitivity of the data or data sharing requirements. These data require an application. Once your application is approved, researchers will access and use the data inside ICPSR’s secure computing environment, called our Virtual Data Enclave (VDE). Click the “Apply for Access” button below to apply through our application portal.</li>
</ul>
000000031 650__ $$asocial media
000000031 650__ $$apolitical attitudes
000000031 650__ $$apolitical behavior
000000031 650__ $$aelections
000000031 651__ $$zUnited States
000000031 655__ $$aweb platform data
000000031 720__ $$aMeta Platforms, Inc.$$eData Collector$$7Organizational
000000031 791__ $$tAsymmetric ideological segregation in exposure to political news on Facebook$$aJournal Article$$whttps://doi.org/10.1126/science.ade7138$$2DOI
000000031 8564_ $$yData dictionary$$9d9975640-6a64-49b7-9a30-d97d2af2698d$$s44149$$uhttps://socialmediaarchive.org/record/31/files/data_dictionary_political_segregation_paper.xlsx
000000031 8564_ $$yVariable descriptions$$960f335a3-c32f-40ce-bfc7-9921ce3027c9$$s76863$$uhttps://socialmediaarchive.org/record/31/files/variables_political_segregation_paper.csv
000000031 8564_ $$yProject-level codebook$$9783c95c1-0176-486c-b3d3-3e102b931359$$s724746$$uhttps://socialmediaarchive.org/record/31/files/US2020_FB%26IG_Elections_External_Codebook.pdf
000000031 8564_ $$yGlossary of terms$$9709b7009-7bc6-4ced-a85f-f31e96f4f02e$$s33969$$uhttps://socialmediaarchive.org/record/31/files/US2020_Glossary.xlsx
000000031 906__ $$a2020-09-01$$b2021-02-01
000000031 908__ $$aFacebook
000000031 910__ $$auser behavior tracking
000000031 912__ $$aSee the codebook for details on the experimental design.
000000031 914__ $$aDownload the data dictionary for variables present in this dataset.
000000031 930__ $$ahttps://icpsr.atlassian.net/servicedesk/customer/portal/53
000000031 980__ $$aFacebook
000000031 980__ $$aDatasets
000000031 980__ $$aUS2020
000000031 981__ $$aPublished$$b2023-07-27