Optimization of Knowledge Sharing in Complementary and Alternative Medicine Social Networks by Filtering Information Seeker Preferences

Social Networks are an efficient way to share knowledge about various topics such as Complementary and Alternative Medicine. However, the amount of information that can be obtained, associated with the variety of information sources and formats present on social networks, is time consuming for the users. We are here focusing on the preferences that Information Seekers have in the CAM area and observing that each of them possess variation in preferences of Information Provider attribute and Information Format type. We are then design a filtering tool adapted to CAM social networks able to customize the design and layout in function of those preferences.