000000037 001__ 37
000000037 005__ 20240801202638.0
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 Restricted.
<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>Restricted data files require a Restricted Data Application and will be accessed through a secure virtual data enclave. <a href="https://docs.google.com/document/d/1NcohZjrhh_F_GpbdArI7DvHBB1adZ80ojFzhy7zvBM4/edit?usp=sharing ">Learn more about applying for restricted data.</a></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$$aJournal Article$$2DOI$$whttps://doi.org/10.1126/science.ade7138
000000037 8564_ $$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://somar.infoready4.com/#freeformCompetitionDetail/1910437
000000037 980__ $$aFacebook
000000037 980__ $$aU.S. 2020 Facebook and Instagram Election Study
000000037 980__ $$aDatasets
000000037 980__ $$aUS2020
000000037 981__ $$aPublished$$b2023-07-27