Sosyal Ağ Yapılarının Değerlendirilmesi Üzerine Odaklanan Modellerin İncelenmesi

• Published in: İşletme Bilimi Dergisi Vol. 3; no. 2; pp. 1 - 17
• Main Authors: Seçkin Codal, Keziban, Coşkun, Erman
• Format: Journal Article
• Language: Turkish
• Published: Sakarya üniversitesi 2015; Sakarya University
• Subjects: ICT Information and Communications Technologies; Social Network Analysis; Multinomial Logit Model; Exponential Random Graph Models; Stochastic ActorBased Models; Relational Event Framework
• ISSN: 2147-6276; 2148-0737

In recent years, many studies are performed in terms of social network to understand and model the decision of actual individual event. Computer-based communication, digital data storage, user interactive dynamic structure offered by Web 2.0 technologies and new data sources offered by social networking sites have led to the emergence of interesting research questions. Thus, the scientific researches focused on modeling of structural effects in social networks has gained importance recently. The study is a theoretical work, in which modeling of social network structures in dynamic environment is examined. Although, this subject has a wide range of application areas, limited number of studies exist in the literature. This may be due to the absence of the categorization in which perspective models analyze the change in network. In this study, four major models are discussed for the evaluation of the social structure in dynamic environment. These models, which are discussed in historical perspective, are examined in terms of their theoretic structure. Then, the discussed models are categorized according to their general application areas, structure of the dataset, model components and the type of change in network. Based on this study, future works that will focus on the analysis of network and behavior dynamics in social network; multinomial logit model could be used for the selection process, exponential random graph model would help for the graphical representation of the network change, stochastic actor-based model could demonstrate the change of network and behavior and relational event framework model might be useful when the specific incident is important rather than the actor.