Social Science Social Media Collaborative

This project seeks to integrate social science and computer science tools to unlock new forms of data for social research. A group of collaborators at the University of Michigan and Georgetown University have been working together on a series of efforts related to analyses of social media, survey, and news content data to understand how we can best examine these forms of data and to answer key social questions.

Visit the S3MC project website

Related Content:

Lies and presidential debates: How political misinformation spread across media streams during the 2020 election
More recalled Biden as winning the election
More recalled Biden as winning the election
As the campaign closes, coronavirus remains the main event
As the campaign closes, coronavirus remains the main event
Once again, Trump’s coronavirus diagnosis dominates news about the campaign
Once again, Trump’s coronavirus diagnosis dominates news about the campaign
Attention to Campaign Events: Do Twitter and Self‐Report Metrics Tell the Same Story?
Harris dominated the conversation in the lead up to the convention
Harris dominated the conversation in the lead up to the convention
Words That Matter: How the News and Social Media Shaped the 2016 Presidential Campaign
Relations Between Variables and Trends Over Time in Rdd Telephone and Nonprobability Sample Internet Surveys
Social Media as an Alternative to Surveys of Opinions About the Economy
Who’s Tweeting About the President? What Big Survey Data Can Tell Us About Digital Traces
Why Don’t Tweets Consistently Track Elections? Lessons from Linking Twitter and Survey Data Streams
The Stability of Economic Correlations over Time: Identifying Conditions under Which Survey Tracking Polls and Twitter Sentiment Yield Similar Conclusions
Those who love Trump and those who hate him are paying the most attention to him
The Kavanaugh saga reminded Republicans of a big reason to vote in November: Stopping Democrats

With Jaren Haber, Lisa Singh, Ceren Budak, Meena Balan, Ryan Callahan, Rob Churchill, Brandon Herren, and Kornraphop Kawintiranon. 2021. Harvard Kennedy School Misinformation Review 2(6). doi: https://doi.org/10.37016/mr-2020-84

CNN – Breakthrough Project

CNN – Breakthrough Project

CNN – Breakthrough Project

With Lisa O. Singh, Yifang Wei, Stuart N. Soroka, Jonathan M. Ladd, Michael W. Traugott, Ceren Budak, Leticia Bode, and Frank Newport. 2020. In Big Data Meets Survey Science: A Collection of Innovative Methods (Craig A. Hill, Paul P. Biemer, Trent D. Buskirk, Lilli Japec, Antje Kirchner, Stas Kolenikov, Lars E. Lyberg, eds.). 193-216. doi: https://doi.org/10.1002/9781118976357.ch6

CNN – Breakthrough Project

with Bode, L., Budak, C., Ladd, J.M., Newport, F., Singh, L.O., Soroka, S.N., & Traugott, M.W. (2020). Washington, D.C.: Brookings Institution Press.

with Krosnick, J.A. (2020). Journal of Survey Statistics and Methodology, 8 (1) 37–61. https://doi.org/10.1093/jssam/smz059

with Conrad, F.G., Gagnon-Bartsch, J.A., Ferg, R.A., Schober, M.F., & Hou, E. (2019). Social Science Computer Review. https://doi.org/10.1177/0894439319875692

with McClain, C.A., Newport, F., & Marken, S. (2019). Social Science Computer Review. https://doi.org/10.1177/0894439318822007

with Dailey, J. (2018). In Stroud, N.J. & McGregor, S. (eds) Digital Discussions: How Big Data Informs Political Communication. https://www.taylorfrancis.com/books/e/9781351209427/chapters/10.4324/9781351209434-5

with Yan, H.Y., Conrad, F.G., Newport, F., & Marken, S. (2018). Public Opinion Quarterly 82 (3), 470-492. https://doi.org/10.1093/poq/nfy030

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