Phase II year
2018
(last award dollars: 2022)
Phase II Amount
$3,166,299
The proposed project seeks to develop an end-to-end data driven system to estimate the effects of historical and forecast the effects of future deterrent courses of action (COAs) against Gray Zone challengers. US conventional military power regularly deters adversaries from employing large-scale conventional forces against US interests; however, this success often motivates adversaries to pursue Gray Zone strategies short of conventional war to achieve their political objectives. The proposed system integrates multi-disciplinary theories and multi-perspective data to understand and forecast the direct and indirect effects of US whole of government deterrent tactics and strategies to deter Gray Zone aggressors. Specifically, the project will assess the causal impacts of US COAs. The system will employ adaptive ensemble models to forecast the effects of COAs in current and future Gray Zone contexts. The project will combine advanced algorithms and empirically driven methodologies with social science theories and expertise to measure and generate influence to successfully deter Gray Zone challengers. The project will assess the range of Gray Zone threats to better understand and adapt to the Gray Zone landscape. ---------- In the modern Information Environment, adversaries deliver misinformation and exploit misinformation to gain geopolitical power and influence over one another. Adversaries do so by via messaging (e.g., blogs, tweets, and other online multimedia communications). Analysts require tools to make sense of such communications, and, more specifically, tools that can measure the direct and indirect influence of individual messages, messaging campaigns, and specific users/messengers. The objective of this project is to develop, mature, and apply state of the art empirical causal analysis algorithms to measure the effectiveness of courses of action (COAs) within the information operations domain. The project concentrates on measuring the impact of messages (i.e., information COAs) and attributes of messages on the larger population's attitudes and beliefs. Furthermore, the project extends analysis to how such changes in attitudes affect real world offline behavior such as social mobilization, radicalization, protests, and riots.
