With the rise of Big Data and the tools of data science, researchers have begun to develop new predictive algorithms on people and society, making inferences about their health, well-being and livelihoods from vast streams of data. This research program will examine the scientific validity of an increasingly popular though experimental approach that makes inferences about individual and societal well-being from sentiment analysis of publicly available social media data. If validated, such a social media indicator of well-being would be a valuable aid to policymakers in evaluating the impact of new policies, but might also aid adversaries in evaluating their efforts to harm or disrupt a populace. Understanding how well predictive algorithms like this work will help policymakers better understand the risks of mass self-disclosure online, and will contribute to a more expansive vision of cybersecurity, which includes the harnessing of new data sources to understand and promote social well-being. The grant will support a pilot study to evaluate the viability of the research design and procedures for a planned large-scale validity study.
