01793nas a2200145   4500008003900000245007100039210006900110300001400179520131900193100001901512700002001531700001901551700002101570856005601591       2012                          d00aClassifying Trust/Distrust Relationships in Online Social Networks0 aClassifying TrustDistrust Relationships in Online Social Network  a552–5573 aOnline social networks are increasingly being used as places where communities gather to exchange information, form opinions, collaborate in response to events. An aspect of this information exchange is how to determine if a source of social information can be trusted or not. Data mining literature addresses this problem. However, if usually employs social balance theories, by looking at small structures in complex networks known as triangles. This has proven effective in some cases, but it under performs in the lack of context information about the relation and in more complex interactive structures. In this paper we address the problem of creating a framework for the trust inference, able to infer the trust/distrust relationships in those relational environments that cannot be described by using the classical social balance theory. We do so by decomposing a trust network in its ego network components and mining on this ego network set the trust relationships, extending a well known graph mining algorithm. We test our framework on three public datasets describing trust relationships in the real world (from the social media Epinions, Slash dot and Wikipedia) and confronting our results with the trust inference state of the art, showing better performances where the social balance theory fails.1 aBachi, Giacomo1 aCoscia, Michele1 aMonreale, Anna1 aGiannotti, Fosca  uhttp://dx.doi.org/10.1109/SocialCom-PASSAT.2012.115