EAGER: Collaborative: Language-Action Causal Graphs for Trustworthiness Attribution in Computer-Mediated Communication

佛罗里达州立大学和康奈尔大学的这项合作研究旨在从基于文本的消息中识别语言行为特征，这些特征可以用来动态推断社交行为者感知的可信度。该团队将研究使用最优分析技术来校准可信度推理，该推理可用于对网络空间中参与者的欺骗行为进行计算建模，并根据他们的言行推断参与者的意图。这项研究将通过观察语言-行为特征和心理社会信任归因机制来理解信任关系的动态。这项研究是一个社会技术方案的先驱，它将促进国家安全和保护普通民众的数据，同时也保护个人的隐私权。这项研究将有助于网络安全科学的发展，并将有助于网络安全社区系统地理解和实现计算机中介群体之间的可信通信和协作信息行为。

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.