Self and social network behaviours of users in cultural spaces

摘要

Many cultural spaces offer their visitors the use of ICT tools to enhance their visit experience. Data collected within such spaces can be analysed in order to discover hidden information related to visitors' behaviours and needs. In this paper, a computational model inspired by neuroscience simulating the personalised interactions of users with cultural heritage objects is presented. We compare a strengthened validation approach for neural networks based on classification techniques with a novel proposal one, based on clustering strategies. Such approaches allow us to identify natural users' groups in data and to verify the model responses in terms of user interests. Finally, the presented model has been extended to simulate social behaviours in a community, through the sharing of interests and opinions related to cultural heritage assets. This data propagation has been further analysed in order to reproduce applicative scenarios on social networks.