Vaitsa Giannouli & Stanislava Yordanova Stoyanova 
Greek University Students’ Real-Life Friendships 
Social Network Analysis and Data Mining

While there is a growing body of research on friendship networks analysis, there is still a dearth of knowledge for Greek friendship networks. Greek students’ friendship networks were studied here by means of a name generator and a name interpreter by applying a social network analysis procedures and data mining. The studied social network consisted of 451 Greek students (Egos) and their 1, 804 friends (Alters). The hypothesis that most friends shared a lot of common features (the same social categorisation and status) was supported partly by the research findings. Most friends shared the same national identity, language, occupation – students, urban location, and religion, but homophily in age and gender belonging was not strongly expressed. Gender belonging differentiated Greek students’ friendships in relation to more female self-disclosure and more frequent contacts in male Ego networks. In addition, there were some repeated patterns in the students’ friendship networks in Greece, such as some small and isolated components consisting of the individuals who were related only in the subgraph, according to the "small world model". There were also some related components consisting of the individuals whose friends were also the friends of some other studied individuals, according to the "preferential attachment model" and the "social balance theory". Greek students’ friendships were characterised by frequent and personal communication between Greek students and discussing politics. Data mining revealed some role attributes such as age belonging and territorial identity, which differentiated the activities performed by the friends. However, no discrimination trends related to gender belonging, nor to an ethnic background. Future research should not only compare the form of the friendship networks in Greece and in other countries, but also elucidate the factors that alter them.