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Data from Facebook, Instagram study on 2020 presidential election released
The Social Media Archive at the University of Michigan Institute for Social Research has released data focusing on the impact of Facebook and Instagram on key political attitudes during the U.S. 2020 elections.
The U.S. 2020 Facebook and Instagram Election Study is a partnership between Meta researchers and independent external academics. The project is led by Talia Stroud of the University of Texas and Joshua Tucker of New York University, who selected 15 additional researchers to collaborate on this effort.
The data from the Social Media Archive (SOMAR) offers new insights and perspectives into some of the most important questions around the role of social media in democracy today. Does social media make us more polarized as a society, or merely reflect the divisions that already exist? Does it help people to become better informed about politics, or less? And how does social media affect people's attitudes towards government and democracy?
It is now available to the broader research community to extend these analyses and validate the findings of research set to be published in peer-reviewed journals in 2023 and beyond. To receive notifications about any additional datasets published in the U.S. 2020 Facebook and Instagram Study, sign up for email updates from SOMAR.
Both Science and Nature are publishing a group of papers linked to the U.S. 2020 Facebook and Instagram Study.
The U.S. 2020 datasets can be accessed via SOMAR's Virtual Data Enclave. Access to these data requires an application. Researchers interested in analyzing the data should begin their application process on SOMAR's Data Applications platform.
SOMAR is part of the Inter-university Consortium for Political and Social Research, a center within U-M's Institute for Social Research. It is a new data archive dedicated to making social media data accessible and useful to researchers like never before. Its mission is to create a platform that allows researchers to work with and analyze social media data, enabling them to study social media behavior, patterns, and trends.
More information: Andrew M. Guess, How do social media feed algorithms affect attitudes and behavior in an election campaign?, Science (2023). DOI: 10.1126/science.abp9364. www.science.org/doi/10.1126/science.abp9364
Sandra González-Bailón, Asymmetric ideological segregation in exposure to political news on Facebook, Science (2023). DOI: 10.1126/science.ade7138. www.science.org/doi/10.1126/science.ade7138
Andrew M. Guess, Reshares on social media amplify political news but do not detectably affect beliefs or opinions, Science (2023). DOI: 10.1126/science.add8424. www.science.org/doi/10.1126/science.add8424
Brendan Nyhan, Like-minded sources on Facebook are prevalent but not polarizing, Nature (2023). DOI: 10.1038/s41586-023-06297-w. www.nature.com/articles/s41586-023-06297-w
Provided by University of Michigan
