I do computational social science at Stanford. My overall interest is the Internet's impact on ideological fracturing around the world. I'm responsive to emails, interested in collaborating, and always happy to talk.
My current work utilizes the Screenomics approach: analyzing hyper-rich behavioral data collected from the smartphone. See a recent New York Times article about my lab's work. Currently, I am running a national online field experiment in the US measuring the impact of social media on political hostility. Separately, with collaborators at Microsoft Research, I am using panel data from the Nielsen company to measure echo chambers in TV news consumption.
Reeves [… Muise…] et al. (2019). Screenomics: A Framework to Capture and Analyze Personal Life Experiences and the Ways that Technology Shapes Them. Human Computer Interaction. 1-52. New York Times report
Muise, Daniel and Pan, Jennifer. 2018. "Online Field Experiments." Asian Journal of Communication 1-18. (DOI)
Kingsley, David and Daniel Muise. 2017. "More Talk, Less Need for Monitoring."The Journal of Experimental Political Science 1-19. (DOI)
Muise, Daniel and Kobbi Nissim. 2016. "Differential Privacy in Descriptive Statistics: a Guidebook for Social Scientists." Privacy Tools for Sharing Research Data Project. (online access)
Muise, D., Howland, B., Rothschild, D., Mobius, M., Watts, D. (2020). Echo Chambers in the Television News Audience: Evidence from Three Years of Nielsen Panel Data. International Communication Association , Gold Coast, Australia.
Muise, D., Hosseinmardi, H., Howland, B., Rothschild, D., Mobius, M., Watts, D. (2020). Growing Separation in the Television News Audience Computation + Journalism , Boston, MA.
Cho, M., Muise, D. (2019). A Study of Factual Information Consumption on Smartphones: Demographics, Time of Use, and Online Media Platforms. Chinese Communication Society , Taipei, Taiwan.
Lu, Y., Muise D., Pan, J., Reeves, B. (2018). Micro-Level Natural Interaction with Information Systems: An International Screenshot Ethnography. International Communication Association's 68th Annual Conference , Prague, Czech Republic.
Muise, D., Reeves, B., and Pan, J. (2017). ``What is News?" Realigning the News Definition with Millions of Consumer Screenshots." Computation + Journalism Symposium. Northwestern University. (online access)
Muise, Daniel. 2016. "Information Communication Technology in Myanmar under the Theory of Innovative Enterprise" Student Southeast Asian Studies Conference. Northern Illinois University.. 2016.
Muise, Daniel, Kobbi Nissim, Mark Bun, Victor Balcer. 2015. "Differentially Private Cumulative Distribution Function Evaluation and Development." NSF Site Visit to the "Privacy Tools for Sharing Research Data" Project. John A. Paulson School of Engineering and Applied Science, Harvard University.. 2015.
Muise, Daniel, Kobbi Nissim, Georgios Kellaris. 2016. CDF.PSIdekick: Public R Package for Evaluating, Visualizing and Comparing Algorithms for Creating Differentially Private Cumulative Distribution Functions and Probability Densities. Available on CRAN archive. . 2015. (CRAN)
I'm a member of the Screenomics Lab at Stanford, where we use millions of passively-collected screenshots to analyze content consumption and media behavior. I have three ongoing projects within this lab:
I'm also a member of Project Ratio at Harmony Labs/MSR, where we use large-scale communication data to measure the political influence of modern media. My current work is a network analysis of news audiences seeking to measure the exact size of echo chambers online and offline.
I grew up in lovely Haverhill, Massachusetts
In 2012, I was accepted to the University of Massachusetts-Lowell on a full scholarship, earning two degrees in Political Science and Economics.
In 2014, I traveled to Myanmar for the first of several times, played ukulele live on air at Mandalay FM, and have been studying the country since.
Starting in 2015, I was a research assistant at Harvard University's John A. Paulson School of Engineering and Applied Science. There, I designed empirical tests for differential privacy algorithms. Gary King, a notable methodologist in our field, was a PI on the project.
I also travel: