A model-based framework to automate the analysis of users' activity in collaborative systems

The automated analysis of users' activity in collaborative systems aims at characterizing the collective process established between the participants and contributing to improving the deficiencies that occur during the users' activity and that are identified by means of this characterisation. This type of analysis, however, requires the completion of complex and costly software development tasks such as capturing information about the actions carried out by the users, calculating low and high level variables to characterize the users' work and behaviour and, finally, defining different kinds of interventions to improve the users' experience solving this way all of those problems that have been detected. To enable the automation of these tasks, reducing the required development effort, we propose a framework that allows software developers to specify the processes of analysis of the activity supported by a collaborative system by means of visual languages in a model-based approach and to automate the analysis accordingly. This framework is used in two case studies. Firstly, the framework is applied for the collaboration analysis in a social network system. Secondly, the collaborative programming activity supported by the COLLECE system is analysed using the framework, and the impact of using the framework is then evaluated.