This research introduces the concept of social distance, which is drawn from clustering methods applied to the social network user base; and incorporates distance in the estimation of trust, as well as user-generated ratings. The trust value estimated will serve as a metric for filtering and sorting content of any kind based on the trustworthiness of the creator. The results revealed that it is possible to provide an estimated measure of trust within individuals in a social network, that clustering methods were of significant help into said evaluation, and that the integration of other variables affecting the building of trust. Results also showed that higher rating scores combined with shorter social distances provide satisfactory trust values, while the opposite happened for subjects presenting lower rating scores in combination with longer distances. This study contributes to the current literature on trust estimation and social networks role in such endeavors.
