000000037 001__ 37
000000037 005__ 20250507132855.0
000000037 02470 $$a10.3886/p5f2-j256$$2DOI
000000037 037__ $$aADMIN
000000037 245__ $$aCoexposure to Facebook Posts with Civic News Domains
000000037 251__ $$av1
000000037 269__ $$a2023-07-27
000000037 336__ $$aDataset
000000037 500__ $$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.
000000037 510__ $$aMeta Platforms, Inc. Coexposure to Facebook Posts with Civic News Domains. Inter-university Consortium for Political and Social Research [distributor], 2023-07-27. https://doi.org/10.3886/p5f2-j256
000000037 520__ $$aThe 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-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, political interest.
000000037 536__ $$oMeta Platforms, Inc.
000000037 540__ $$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>
000000037 650__ $$asocial media
000000037 650__ $$apolitical attitudes
000000037 650__ $$apolitical behavior
000000037 650__ $$aelections
000000037 651__ $$zUnited States
000000037 655__ $$aweb platform data
000000037 720__ $$aMeta Platforms, Inc.$$eData Collector$$7Organizational
000000037 791__ $$tAsymmetric ideological segregation in exposure to political news on Facebook$$aJournal Article$$whttps://doi.org/10.1126/science.ade7138$$2DOI
000000037 8564_ $$yData dictionary$$93cd3c73c-a44a-4e41-a100-80cf22f3ba67$$s44149$$uhttps://socialmediaarchive.org/record/37/files/data_dictionary_political_segregation_paper.xlsx
000000037 8564_ $$yVariable descriptions$$98c9096fc-41f6-48df-9426-ec5fefe2a97f$$s76863$$uhttps://socialmediaarchive.org/record/37/files/variables_political_segregation_paper.csv
000000037 8564_ $$yProject-level codebook$$9d9a80caf-6906-4aec-a85b-d83745929851$$s724746$$uhttps://socialmediaarchive.org/record/37/files/US2020_FB%26IG_Elections_External_Codebook.pdf
000000037 8564_ $$yGlossary of terms$$9d7663cc8-417d-4823-a231-8528f43368d6$$s33969$$uhttps://socialmediaarchive.org/record/37/files/US2020_Glossary.xlsx
000000037 906__ $$a2020-09-01$$b2021-02-01
000000037 908__ $$aFacebook
000000037 910__ $$auser behavior tracking
000000037 912__ $$aSee the codebook for details on the experimental design.
000000037 914__ $$aDownload the data dictionary for variables present in this dataset.
000000037 930__ $$ahttps://icpsr.atlassian.net/servicedesk/customer/portal/53
000000037 980__ $$aFacebook
000000037 980__ $$aDatasets
000000037 980__ $$aUS2020
000000037 981__ $$aPublished$$b2023-07-27