Context Specific Modeling of Communicational and Informational Content in Facebook

Context Specific Modeling of Communicational and Informational Content in Facebook

Johannes Schick (University of Münster, Germany), Martin Kuboschek (Informationstechnikzentrum Bund, Germany) and Wolfram Manfred Lippe (University of Münster, Germany)
DOI: 10.4018/978-1-5225-2814-2.ch007


In this chapter, the authors apply context specific methods to formalize communicational parameters for different profile groups in a social network platform, taking Facebook as an example. Information is posted to or shared with distinct user groups. The context specific approach is used to describe informational content of exchanged data and to formalize privacy settings in a social graph. Communicational and informational parameters are specified with direction and communicational content in a context specific model. Relations are defined to model communicational and informational interactions as well as environmental factors taking influence on the profile groups. The textual representation of this approach is introduced to describe models in a text-based form.
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The modeling of social structures has a long tradition in the social science (Freeman, 2004). With the spread of the internet, the formalization of social structures has new significance for the specification of social interactions and data mining. The large amount of distributed data has to be structured and stored. In addition, the modeling of exchanged information between communicators is an interesting aspect. Communicational content provides information about behavior and gains a fast possibility to get and analyze data (Russell 2014). Therefore, the structuring and formalization of these data is an important aspect for further processing.

Social networks are social structures. Vertices can be modeled as individuals and the links between them can be represented as e.g. friendship (Han, Kamber, & Pei, 2012). Modeling languages like Entity-Relationship Modeling (Chen, 1976) have a very intuitive view on the real world, but cannot cover the aim to model high distributed data and data flows in social structures. Graph-based databases have their main focus on the nodes in a graph and the relations between them (Foster, Ghani, Jarmin, Kreuter, & Lane, 2016). Each system of communicators is embedded in an environment. Environmental factors take influence on communicators and their behavior.

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