The last decade has seen the tremendous growth of the so-called Social Web and this trend is expected to continue in the years to come. As the distinction between the Web and the Social Web disappears, more and more people turn to them daily for information related to important medical, financial and political decisions. Therefore, there is an indisputable need for reliable information in the online world. In the years to come, there will be an increase in interaction with real-time information channels (R-TICs), such as the instant interaction, commenting and notification systems that every social network is developing . R-TICs will put new stress to human abilities to act under time pressure in making decisions and determine the quality of the information received. Technology can assist acting with confidence, by maintaining a personalized network of trusted sources and understanding the reasons for trust or distrust of information. The overall aim of this research is to lay the foundation of a comprehensive approach to support critical thinking and increase security while maintaining privacy in a trusted cyber-world. It proposes the design and implementation of an application that can maintain trails of trustworthiness for information propagated through Twitter, but is applicable to other R-TICs. When confronted with information that requires fast action, these applications will enable its users to evaluate its provenance, its trustworthiness and the independence of the multiple sources that provide this information. In addition this proposal will develop an online course for undergraduates and high school students that discuss the epistemological questions of knowledge and explains what critical thinking means in our highly interconnected world, interacting regularly with people we may never meet. In all of the phases of this proposal, undergraduates, under-represented minorities and women will be actively involved.
The core design envisions the testing of these ideas by developing a personalized Twitter client that keeps privately the trust values of its owner. Trustworthiness of a message received is calculated based on implicit and explicit rules: the user may explicitly mark a message as trustworthy or not, and her decisions affect the trust value of its sender in her personal client; or the system will determine a trust value based on the actions of those who have seen and propagated the message to the user, and whose trust values are already known to the user. Message independence is computed based on content search on Twitter and grouped by the inverse distance of the original senders. Privacy of the client's trust values is enhanced by the separation of the global R-TIC network (Twitter) and the user's trust network (the client). Additional research questions can be answered through the use of simulation and is expected that they will be adopted by the R-TIC operators once they see the benefits of the proposed features.
