I am a computational social scientist writing my dissertation at Stanford University's Department of Communication. I study the media psychology of news consumption, and what that means for the measurement of political identity.
I've previously worked for Microsoft Research, Instagram Reseearch, and Facebook's Central Integrity, and I am the founder of KRYSTL media insight.
I am currently seeking full-time positions to start in Summer 2022.
I am a proud member of the talented and interdisciplinary Screenomics Lab, analyzing hyper-rich behavioral data collected from smartphone screenlogging. See a recent New York Times article about the lab's work.
Publications and Working Papers
Muise, Hosseinmardi, Howland, Mobius, Rothschild, Watts (2021). The Exception, not the Rule: Partisan Segregation in the Audiences for Television News and Online News. (Submitted manuscript)
Muise, Pan, Reeves (2021). The Nature of Political Information Exposure on Smartphones and Social Media: Description and Experimental Investigation of Moment-by-Moment Behavior. (Ongoing dissertation)
Muise, Lu, Pan, Reeves (2021). Selectively Localized: Temporal and Visual Structure of Smartphone Screen Activity across Media Environments. (Submitted manuscript)
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, Pan. 2018. "Online Field Experiments." Asian Journal of Communication 1-18. (DOI)
Kingsley, Muise. 2017. "More Talk, Less Need for Monitoring."The Journal of Experimental Political Science 1-19. (DOI)
Muise, 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)
With the Screenomics Lab at Stanford, I have overseen the daily operations of the lab's largest-ever data collection effort, lasting from June 2020 until November 2021. I am also using screenomics data in my dissertation work, which measures the rapidity of political information encounters oin the smartphone in natural device usage. The results of this work will demonstrate that modern `news' consumption is largely reduced to fleeting snippets lasting only seconds. Finally, I am in early stages of building media insight startup KRYSTL, funded by the Brown Institute for Media Innovation.