Context inference from social networks: A tie strength based approach

All online sharing systems gather data that reflects user´s behavior and their shared activities. Relationship degree between two users varies continuously. Static friend list in the social network is unable to express it completely. Tie strength is used to quantitatively describe real social relations. It is based on lots of features derived from activities of a user in social network. We introduce a model to measure tie strength between users in a given context. Here a novel definition of tie strength is introduced which exploits the existence of multiple online social links between individuals. The proposed system infers the context from user´s interaction using the applications of Natural language processing methods and clustering techniques. From this context the tie strength between users are found. This evaluates and analysis the performance of this model.