This collaborative research between Florida State University and Cornell University is to identify language-action features from text-based messages that can be used to dynamically infer a social actor's perceived trustworthiness. The team will investigate using optimal analysis techniques to calibrate trustworthiness reasoning, which can be used to computationally model actors' deceptive behaviors in cyber space and to infer actors' intent based on their words and actions.
This research will have a transformative impact in understanding the dynamics of trusting relationships through observing language-action features and psychosocial trustworthiness attribution mechanisms. This study serves as a precursor to a socio-technical schema that will facilitate national security and data protection for the general populace while also protecting the individual's right to privacy. This study will contribute to the science of cyber-security, and will help the cyber-security community to understand and enable trustworthy communication and collaborative information behavior among computer-mediated groups in a systematic way.
