Abstract: Personalized sorted lists of data items for users within an online social network can be generated. Users within the social network are profiled based on their interests. Concepts are segmented in the ontological database into clusters of concepts that are shared by several user profiles. A social graph is defined in which nodes represent the users within the social network and edges represent the explicit connections between the users. A neighborhood graph for each concept cluster is defined. Multilayered social affinity graphs are defined. Data items acted upon by users within the social network in a given time interval are identified. Users within the social network that have acted upon the identified data items are determined. One or more layers of the social affinity graphs are selected for each identified item. Initial endorsement values in the nodes are injecting for each identified item.