David Muchlinski

I am a computational social scientist specializing in the study of political violence. I utilize computational methods such as supervised and unsupervised machine learning, natural language processing, and deep learning to predict and explian processes related to mass political violence. My current research focuses on explaining how emerging digital technologies such as social media faciliate political radicalization cross-nationally. Currently, I am studying which messages are most likely to radicalize users of this technology into taking violent action by studying extremist online forms and social media platforms and whether radicalization begins in online digital communities or whether disaffected users seek out radical online communities due to experiences offline.

My previous research used machine learning tools to forecast onsets of civil war, electoral violence, and mass atrocities such as genocides and politicides. My research has been published in multiple academic journals including The American Political Science Review, Political Analysis, Political Science Research and Methods, The Journal of Conflict Resolution, Terrorism and Political Violence, Democratization, and Politics and Religion. Prior to joining the faculty at the Sam Nunn School, I was a postdoctoral research associate with the Project on Explaining and Mitigating Electoral Violence at the University of Glasgow and King's College London in the United Kingdom, and with the Atrocity Forecasting Project the University of New South Wales in Sydney, Australia.

I am currenly seeking well-qualified computer science students to assist with my research.  If you are a undergraduate or graduate student in Computer Science, Interactive Computing, Machine Learning, Data Visualization, Network Analysis, or other related field and wish to inquire about research opportunities on important projects related to Computing for Social Good, please feel free to contact me at my email address.