Security and Communication Networks
Group affinity based social trust model for an intelligent movie recommender system
Multimedia Tools and Applications
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Man as a social being, as a being in social relations, is in constant motion [1]. Such mobility affects the social networks that Man builds throughout one's existence. Networks that can consist of dozens, hundreds or even thousands of other people, with various degrees of mobility. During the formation of such networks, problems can arise, such as elements that concentrate many relationships, very isolated individuals or peripheral members of a network, people who are the only link between two distinct groups, agglomerations of people in isolated points. This can cause a series of losses to the most important element that flows through social networks: knowledge. In scientific social networks, this assertion takes even more importance, mainly on account of the mobility of researchers and the excess of knowledge circulating in it, making it more vulnerable to the movements of Man. It is with the intent of solving this problem that our work seeks to achieve success, as it analyzes the scientific social networks based on the GCC tool [9] detects the problems related to them, and suggests recommendations of relationships to users considered harmful to the flow of knowledge in the network. We call this process of Social Network Balancing. For the evaluation of this work we conducted a comparison with several similar proposals, and developed a working prototype, which in turn was used to make our case studies.