CASE — Challenges and Applications of Automated Extraction of Socio-political Events from Text @ACL-IJCNLP

Today, the unprecedented quantity of easily accessible data on social, political, and economic processes offers ground-breaking potential in guiding data-driven analysis in social and human sciences and in driving informed policy-making processes. The need for precise and high-quality information about a wide variety of events ranging from political violence, environmental catastrophes, and conflict, to international economic and health crises has rapidly escalated (Porta and Diani, 2015; Coleman et al. 2014). Governments, multilateral organizations, local and global NGOs, and social movements present an increasing demand for this data to prevent or resolve conflicts, provide relief for those that are afflicted, or improve the lives of and protect citizens in a variety of ways. For instance, Black Lives Matter protests[1] and conflict in Syria[2] events are only two examples where we must understand, analyze, and improve the real-life situations using such data.