Dynamic Community Structure in Online Social Groups

One of the main ideas about Internet is to rethink its services in a user-centric fashion. This fact translates having human-scale with devices that will become smarter and make decisions place their respective owners. Online Social Networks and, particular, Groups, such as Facebook be at epicentre this revolution because great relevance current society. Despite vast number studies on human behaviour Media, characteristics Groups are still unknown. In paper, we propose dynamic community detection driven study structure users inside Groups. The communities extracted considering interactions among members group it aims searching dense communication groups users, evolution over time, order discover social properties analysis carried out activity 17 using 8 algorithms 2 possible interaction lifespans. Results show OSGs very fragmented but tools capable uncovering relevant structures. quality gives important insights increasing lifespan does not necessarily result more clusterized or bigger communities.