Assistant Professor, Department of Defense Analysis
Naval Postgraduate School


Defense Analysis Department


jrhammon <at>

Curriculum Vitae

Google Scholar

Jesse Hammond is an Assistant Professor in the Defense Analysis Department at the Naval Postgraduate School. Dr. Hammond holds a Ph.D in Political Science from the University of California at Davis. His research focuses on political violence, with an emphasis on leveraging innovative data sources and quantitative tools to better understand these complex processes. Dr. Hammond's work has been published in the American Political Science Review, the Journal of Peace Research, International Studies Quarterly, and Social Network Analysis and Mining.

Research interests: Political violence and civil conflict; applied statistics; social network analysis; GIS and spatial modeling; text-as-data.


  • Milazzo, Caitlin, and Jesse Hammond. 2017. "The face of the party? Leader personalisation in British campaigns." Journal of Elections, Public Opinion and Parties, forthcoming.
  • Hammond, Jesse. 2017. "Maps of mayhem: strategic location and deadly violence in civil war." Journal of Peace Research, forthcoming.
  • Bormann, Nils-Christian, and Jesse Hammond. 2016. "A slippery slope: the domestic diffusion of ethnic civil war." International Studies Quarterly 60(4): 587-598.
  • Barnett, George, Ke Jiang, and Jesse Hammond. 2015. "Using coherencies to examine network evolution and co-evolution." Social Network Analysis and Mining 5(1): 53.
  • Hammond, Jesse, and Nils Weidmann. 2014. "Using machine-coded event data for the micro-level study of political violence." Research & Politics 1(2).
  • Engstrom, Erik, Jesse Hammond, and John Scott. 2013. "Capitol mobility: Madisonian representation and the location and relocation of capitals in the United States." American Political Science Review 107(2): 225-240.
  • Barnett, George, Jeanette Ruiz, Jesse Hammond, and Zhige Xin. 2013. "An examination of the relationship between international telecommunication networks, terrorism and global news coverage." Social Network Analysis and Mining 3(3): 721-747.