Promoting learning through social networks supported by a social matching system model

Presently, a plethora of internet service offerings imply in new emerging social behaviors. Learning by following an example is a behavior already investigated in educational theories which this study applies to internet based social networks. Matching people through their common knowledge is a form of leveraging knowledge acquisition by feeding complementary information across those clusters of similar peers. This paper presents a formalized mathematical model mapping a set of learning theories to knowledge interchange inside social networks. The model identifies the best peer matching to a given knowledge among people referring to bookmarked sites. A social matching engine was implemented and used to collect evidence on learning improvements that can achieved through knowledge based peer indications.