My research focuses on using large datasets, primarily social media data, to understand conflict, migration, and polarization. I am particularly interested in the ways in which online data can be used to support vulnerable, diverse, and hard to reach populations, as well as how such information can be combined with survey data and other traditional data sources. Methodologically, I am interested in probabilistic machine learning and natural language processing.
Peer Reviewed Papers:
Displacement and Return in the Internet Era: Social Media for Monitoring Migration Decisions in Northern Syria with Fotini Christia and Kiran Garimella. Forthcoming in World Development. doi.org/10.1016/j.worlddev.2023.106268
Simplistic Collection and Labeling Practices Limit the Utility of Benchmark Datasets for Twitter Bot Detection with John Chris Hays, Zachary Schutzman, Philipp Zimmer, Manish Raghavan. TheWebConf 2023, Best Paper Award. doi.acm.org?doi=3543507.3583214
Social Media Narratives across Platforms in Conflict: Evidence from Syria with Elizabeth Parker-Magyar, Ahmet Akbiyik, Kiran Garimella, and Fotini Christia. Under review. Preprint: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4075120
Predicting individual mortality with traditional and machine learning methods with Luca Badolato, Ari Decter-Frain, Nicholas J. Irons, Maria Miranda, Elnura Zhalieva, Monica Alexander, Ugofilippo Basellini, and Emilio Zagheni.
Scholarly migration and collaboration worldwide: A word embedding representation with Aliakbar Akbaritabar.