Towards knowledge creation and management model over online social networks

Abstract

An online Social network (OSNs) is an active platform of user socialization belonging to different societies and has a subject of interest for researchers. In OSNs, relationships among users and groups are created to share information; and turned out a foundation of knowledge. However, user-generated contents are disseminated, unstructured, and dynamic in nature. As there is no central authority to own and maintain these large numbers of user-generated contents, it is difficult to process and extract knowledge from it. Moreover, it is far challenging to collect, manage, and classify randomly transmitted useful contents and to associate them for the creation of knowledge. Further, in complex networks where graph nodes belong to more than one context or groups, ubiquitous community detection is more challenging in such scattered data formats. In this paper, a model for knowledge creation over online social networks has been presented. The model explores the strength of social relationship, users' online behavior by their interests and hobbies, and the frequency of users participated together in a particular context. It helps in smoother collaboration among users and groups, enhance learning by sharing information, and improve efficiency of the social graphs for community detection. Moreover, based on the available information in different context, the model facilitates efficient decisions, knowledge and innovations in OSNs.