A formalism to measure trust and distrust based on extended structural balance theory
In our upcoming paper on PST 2013 Conference on Privacy, Security and Trust, we introduce a formal theory for measuring trust and distrust. The paper can be found here (<a href="YA_PST2013.pdf">YA_PST2013.pdf</a>).
Our method formalizes the assumptions behind most trust prediction algorithms: structural balance theory (SBT). According to this theory, certain relationships are balanced and do not cause tension. If we use plus to indicate friendship or trust, and minus to represent hatred or distrust, we can consider the above three way relationships.
For example, triangles one and two above are balanced in both strong and weak structural balance theory, and triangle four is unbalanced in both. Weak SBT also considers triangle three as balanced. For example, in triangle four, A and C are two friends of B that cannot get along. This causes tension because B now has to make sure that she does not meet with A and C at the same time. Furthermore, SBT claims that networks tend to converge towards balance as individuals try to reduce the tension in relationships. This logic has been used in many algorithms including clustering methods.
In real life networks, the support for SBT has been mixed. To address this issue, we introduce an extension of SBT (ESBT) that takes into account that the strengths of the ties matter as much as their valance (positive or negative). We introduce a new theory that explains structural balance. In our model, we have a continuum of levels of trust from strong trust to strong distrust. This spectrum also includes weak biases in either direction as well as neutral relations with no bias or preconceived notions. ESBT is based on two basic axioms shown below:
<b>Sunday, June 2, 2013</b>