EAGER

Social media now play an important role in exposing people to information about a wide range of topics ranging from entertainment to hard news and political debate. What can be seen on these platforms is heavily influenced by algorithms that are designed to select the most engaging and relevant content for each user. By seeking to maximize engagement, these algorithms may inadvertently amplify factually dubious or poor quality information that reinforces users' existing beliefs. In doing so, these algorithms could reduce the diversity of information to which users are exposed.

Social and behavioral research has a long history of collecting digitized data. With more and more studies incorporating participants' smartphone sensor and usage data, individual privacy has become a serious concern. Although researchers are trained to exercise confidentiality, sensitive information can be inferred from the smartphone data about the participants and their environment (e.g., families and communities). Without a systematic solution to address privacy concerns, participants may withdraw and request removal of their data from studies.

Network and Security Operations Centers (SOCs) are central components of modern enterprise networks. SOCs manage network operations, defend against cyber threats, and maintain regulatory compliance. Typically, management and SOC operators use monitoring software and metrics, such as open and closed tickets, to manage SOC efficiency. These metrics may fail to represent the real effectiveness of the SOC and the security posture of the network.

Bug bounty programs were once a novel way to encourage security researchers to report vulnerabilities. They are now common. Hundreds of organizations--from car manufactures to the Department of Defense--now operate bug bounty programs that purchase flaws from independent vulnerability researchers. Yet, while bug bounty programs are widely viewed as a promising strategy for reducing software attack surfaces, unsolved social and technological issues can limit the efficacy of these programs.

This project integrates advances in data science and key findings from psychological research to improve the prediction of trust in information on social media by modeling the psychological phenomenon known as the memory illusion. The memory illusion refers to memory errors that people make to remember information as an outcome of interpreting and making inferences from their past experience. This project will use social media data to examine the memory illusion with online information, and to understand how it is associated with people's trust in information on social media.