Representacão, extração e avaliação de interações entre usuários de redes sociais online

Abstract

The interest in understanding user interactions is increasing with the popularity of Online Social Networks. This scenario leads to rich opportunities to improve the design of interfaces, to understand the organization of social movements, to model the dynamics of viral marketing and to characterize the distribution of multimedia content, among others. In the investigation of these research opportunities, a widely used representation of users activities is based on graphs as underlying data models. Graph data models usually consider a specific interaction, which is analyzed based on the interpretation of statistical measures and graph-based measures. On the other hand, user activities and possibilities of interaction in social networks are multifaceted, so that singleinteraction graph-based approaches might prove to be unfeasible to properly model the problem. In order to deal with these limitations, data mining techniques may be employed as an alternative to graph-based modeling approaches, by enabling extraction and evaluation of users activities as patterns. However, both in the use of the model graph-based as in the use of data mining techniques, the literature reports an implicit representation of elements associated with the users activities such as executed actions, shared media, used applications and devices. In this scenario, there is a demand for a descriptive model which allows explicit representation of the elements associated with users activities - this representation can be used in the extraction and evaluation of interactions among users. To meet this demand, this thesis presents a technique and a method to represent, to extract and to evaluate interactions among users of Online Social Networks. Results of experimentation of applying the technique and method based on data obtained from an Online Social Network are also reported.