A Multi-agent Framework for the Analysis of Users Behavior over Time in On-Line Social Networks

The number of people using on-line social networks as a new way of communication is continually increasing. The messages that a user writes in these networks and his/her interactions with other users leave a digital trace that is recorded. In order to understand what is going on in these virtual environments, it is necessary to use systems that collect, process, and analyze the information generated. Currently, there are tools that analyze all the information related to an on-line event once the event finished or on a specific point of time (i.e., without considering the evolution of users' actions during the event). In this article, we present a multi-agent system (MAS) that deals with the analysis of the evolution of users' interactions in events on on-line social networks during a period of time. The system offers a complete vision of what is happening in an event. We evaluated its functionality through the analysis of a set of events on Twitter.