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I currently work at the Department of International Relations, Ozyegin University and serve as a fellow at the Carnegie Endowment for International Peace. Previously, I was a dual non-resident fellow at Oxford University's DPIR and the Alan Turing Institute, London. I'm interested in how greater interdisciplinarity and hybrid research methods improve our understanding of world affairs. Current focus: how technology affects human conflict online and offline.
Do you think R and Python should be taught together in a master's level social data science course, or should the course pick one and focus on it? Let's assume students have some background with Excel and have minimal training in R or Python.
This is an 'umbrella project' that seeks to explore themes and sub-themes of how digital communication technologies and related research methods influence and impact the field of International Relations. Some of the research streams include the impact of computational methods on conflict and behavioural research related to diplomacy, violence and inter-state competition.
Existing attempts to model civil conflicts, like those in Ukraine and Syria, are not currently reliable as they are often not data driven, or only rely on data provided by the states. The large volumes of open Internet and social media data available has the potential to rethink the way civil wars are modelled. How can we simulate and model civil conflicts in a data-driven way, to understand the dynamics of these events?
This project makes a time-series overview of A.I.-based military adaptation events over the last decade. It provides a typology of 'A.I.-based weaponization' dynamics, policies and tools and gradually constructs a dataset that will be used for future publications. The GAIA dataset will be open to public and academic use once completed.