Modelling User's Location Check-ins on Location-Based Social Networks

Location Based Social Networks (LBSN) attracts millions of people; they share the location they visit via their smartphones. The main purpose of the check-in option is to give information about the place you visited to the other users. Accumulated check-ins in the LBSN, provide a lot of opportunities to study the temporal-spatial and social behaviour of the user. With this information we can have an overview about important inner city locations, disease areas, and human mobility. The aim of this paper is to predict the next move of the user by examining his/her historical statement. Before modelling human mobility, the basic information about LBSN is going to be analysed and then by the help of four methods, human mobility is going to be modelled. All these models are then going to be analysed based on their categories before a prior notice is set. User's next check-in category estimation will be followed by his/her next check-in location indication. Then a comparison is being made considering the models' prediction success.