Homa Hosseinmardi


Homa Hosseinmardi

Associate Research Scientist

Homa Hosseinmardi is a visting scholar and lead of the Penn Media Accountability Project (PennMAP). She is also an assistant professor at UCLA. 

Homa researches the intersection of computational social science, statistical inference, and applied machine learning. She is motivated by how advances in sensing technology and the availability of large-scale data, coupled with computational methods, can help to answer fundamental questions from individual well-being and affect to political polarization and media echo chambers. Her research agenda makes extensive use of applied machine learning; applied statistics; social, behavioral, and political science; and human-centered approaches.

Home received her PhD in Computer Science from the University of Colorado Boulder and worked in Danaher Labs in 2015-2017 as a Data Scientist. Before joining the CSSLab, she was a postdoctoral research associate at the Information Sciences Institute, where she worked with Emilio Ferara. Homa also contributes as an external researcher at the CU CyberSafety Research Center.

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7 entries « 1 of 2 »

Ribeiro, Manoel Horta; Hosseinmardi, Homa; West, Robert; Watts, Duncan J.

Deplatforming did not decrease Parler users’ activity on fringe social media Journal Article

In: PNAS Nexus, vol. 2, iss. 3, 2023.

Abstract | Links | BibTeX

Muise, Daniel; Hosseinmardi, Homa; Howland, Baird; Mobius, Markus; Rothschild, David; Watts, Duncan J.

Quantifying partisan news diets in Web and TV audiences Journal Article

In: Science Advances, vol. 8, iss. 28, 2022.

Abstract | Links | BibTeX

Hosseinmardi, Homa; Ghasemian, Amir; Clauset, Aaron; Mobius, Markus; Rothschild, David M.; Watts, Duncan J.

Examining the consumption of radical content on YouTube Journal Article

In: Proceedings of the National Academy of Sciences, vol. 118, no. 32, 2021.

Abstract | Links | BibTeX

Ghasemian, Amir; Hosseinmardi, Homa; Galstyan, Aram; Airoldi, Edoardo; Clauset, Aaron

Stacking models for nearly optimal link prediction in complex networks Journal Article

In: Proceedings of the National Academy of Sciences, vol. 117, no. 38, pp. 23393-23400, 2020.

Abstract | Links | BibTeX

7 entries « 1 of 2 »