A social network defines the structure of a social community like an organization or institution, covering its members and their inter-relationships. Social relationships among the members of a community can be of different types like friendship, kinship, professional, academic etc. Traditionally, a social network is represented by a directed graph. Analysis of graph structure representing a social network is done by the sociologists to study a community. Hardly any effort has been made to design a data model to store and retrieve a social network related data. In this paper, an object-relational graph data model has been proposed for modeling a social network. The objective is to illustrate the power of this generic model to represent the common structural and node-based properties of different social network applications. A novel multi-paradigm architecture has been proposed to efficiently manage the system. New structural operators have been defined in the paper and the application of these operators has been illustrated through query examples. The completeness and the minimality of the operators have also been shown.
A social network is a social structure between actors (individuals, organization or other social entities) and indicates the ways in which they are connected through various social relationships like friendships, kinships, professional, academic etc. Usually, a social network may represent a network of acquaintance between people, a club and its members, a city or village communities, a research group communicating over Internet or a group of people communicating with each other through e-mail messages (Cai, 2006; Long & Siau, 2007). Recently, World-Wide-Web or just Web, as it is popularly known, has played a major role in the formation of communities (Cyber-communities or Web communities) where the members or people from different parts of the globe can join the community for common interest. For example, members of an IEEE society communicating with each other through e-mail may form a web-community. Social network applications include the traditional social network applications as studied by the social scientists (Hanneman, 2001; Holland & Leinhardt, 1979; Leinhardt, 1977), network of acquaintances or referral system as proposed in (Yu & Singh, 2003; Kuatz et.al, 1997) and finally the Web community (Newman, 2003; Hanneman, 2001). Incidentally, in a referral system, each actor in the social community provides a set of links to its acquaintances that in turn become members of the community. In the same way, these new actors bring their acquaintances to the community again. Thus, the social network keeps on growing. This view of social network has given rise to different commercial applications like LinkedIn.com, Ryze.com, Tribe.net etc. (http://www.Tribe.com). For example, a commercial referral network on the web may offer employment services, where actors provide information like qualification, experience etc. Similarly, another referral network may offer matrimonial services, where actors provide information like, age, marital-status, sex, monthly earning etc.
Social networks can have a few or many actors, and one or more kinds of relations between pairs of actors. For example, two houses of a village community may be connected to each other because of a family relationship yielding a kinship relation or they may communicate for lending or borrowing money generating an economic relationship. Two actors of a social network may even be connected by more than one relation. For example, an actor i may refer to another actor j, since they belong to the same professional area (e.g. computer scientist), and at the same time they may also be connected by another relation like the same hobby (e.g. playing baseball).
To build a useful understanding of a social network, a complete and rigorous description of a pattern of social relationships is a necessary starting point for analysis. This pattern of relationships between the actors can be better understood through mathematical or formal representation like graphs. Therefore, a social network is represented as a directed graph or digraph. In this graph, each member of a social community (people or other entities embedded in a social context) is considered as a node and communication (collaboration, interaction or influence) from one member of the community to another member is represented by a directed edge. In order to understand the social properties and behavior of a community, social scientists analyze the corresponding digraph. The number of nodes in social network applications can be very few representing a small circle of friends or very large representing a Web community. This graphical representation is useful for the study and analysis of a social network. In addition, each social network will also have some node related information depending on the application area or the type of social community the network is representing. For example, in a village community, each node may represent a household in the village with data relevant to such houses.