Community Detection in Social Networks

Analiza društvenih mreža postala je vrlo dinamično i unosno područje pojavom online društvenih mreža i povećanjem kapaciteta za njihovu obradu. Otkrivanje zajednica jedno je od najvažnijih područja unutar analize društvenih mreža. U ovom radu, predstavljen je pojam društvene mreže, njene karakteristike, pojam zajednice u kontekstu društvenih mreža i problematika procjene njihove kvalitete. Nadalje, napravljena je usporedba Girvan-Newman, Label Propagation i Clauset-Newman-Moore algoritama za otkrivanje zajednica. Analiza je provedena u dva dijela: prvo na umjetno generiranim mrežama proizvedenih Lancichinetti-Fortunato-Radicchi metodom, a potom na stvarnim podacima s društvene mreže Twitter. The arrival of online social networks and the increase in the capacity to process them has caused social network analysis to become a very dynamic and lucrative field. Community detection is one of the most important areas of social network analysis. This thesis presents the notion of a social network, its characteristics, the notion of community in the context of social networks and the problem of assessing their quality. Furthermore, a comparison of Girvan-Newman, Label Propagation and Clauset-Newman-Moore community detection algorithms was made. The analysis was performed in two parts: first on artificially generated networks produced by the Lancichinetti-Fortunato-Radicchi benchmark, and then on real data from the social media network Twitter.