The fast-evolving business practice and the continuously changing users’ profiles attract researchers’ interest, such as Brandtzaeg et al. (2010), Brandtzaeg et al. (2007), Constantinides (2011), and Hsuan (2008). However, the current classification studies allow for users’ segmentation in specific social media applications and only one at a time (e.g. SNS, blogs). Thus, Beemt et al. (2010) and Brandtzaeg et al. (2010) called for integrated classification research. The study addresses the gap in users’ segmentation within all social media applications exploring how Greek users could be classified according to their “motivation of use”, “usage patterns” and “social identity” (n=270). This is the first study that attempts to classify users on the basis of their common demographics (age, gender, educational level, income, and marital status), motivations of use, behavioral patterns - such as frequency of use and usual activities-and social identity in the environment of all social media types. The present study explores users’ behavior (n=270) by providing a classification scheme along with detailed profiling of the resulting clusters. Implementing cluster analysis results indicated that users can be classified into three categories (“Information Seekers”, 27%, - “Operational and Psychological Boost Benefits Seekers”, 47 %- “Communication Seekers”, 26%). The “social identity” factor was also used through Anova Test presenting noteworthy differences among the emerging clusters. The current research contributes to develop a users’ classification scheme treating social media as one single category. The paper ends by providing theoretical and managerial implications serving helpful insights about social media patterns.
Keywords: Social media users' segmentation, social identity, social media behavior, e-communicatio
