Social Networking Analysis Kevin Curran and Niamh Curran Abstract A social network indicates relationships between people or organisations and how they are connected through social familiarities. The concept of social net- work provides a powerful model for social structure, and that a number of important formal methods of social network analysis can be perceived. Social network analysis can be used in studies of kinship structure, social mobility, science citations, con- tacts among members of nonstandard groups, corporate power, international trade exploitation, class structure and many other areas. A social network structure is made up of nodes and ties. There may be few or many nodes in the networks or one or more different types of relations between the nodes. Building a useful understanding of a social network is to sketch a pattern of social relationships, kinships, community structure, interlocking dictatorships and so forth for analysis. 1 Introduction Communication is and has always been vital to the growth and the development of human society. An individual’s attitudes opinions and behaviours can only be characterised in a group or community [5]. Social networking is not an exact science, it can be described as a means of discovering the method in which problems are solved, how individuals achieve goals and how businesses and operations are run. In network theory, social networks are discussed in terms of node and ties (see Fig. 1). Nodes are individual actors and ties are relationships within networks. The social capital of individual nodes/actors can be measured through social network diagrams, as can measures of determination of the usefulness of the network to the actors individually [4]. The shape of a social network helps determine a network’s K. Curran (B) · N. Curran School of Computing and Intelligent Systems, Faculty of Computing and Engineering, University of Ulster, Northern Ireland, UK e-mail: [email protected] N. Bessis and C. Dobre (eds.), Big Data and Internet of Things: 367 A Roadmap for Smart Environments, Studies in Computational Intelligence 546, DOI: 10.1007/978-3-319-05029-4_15, © Springer International Publishing Switzerland 2014 368 K. Curran and N. Curran Fig. 1 Social networking diagram usefulness to its individuals. Smaller, tighter networks can be less useful to their members than networks with lots of weak ties to individuals outside the main network. More open networks, with many weak ties and social connections, are more likely to introduce new ideas and opportunities to their members than closed networks with many redundant ties. In other words, a group of friends who only do things with each other already share the same knowledge and opportunities. A group of individuals with connections to other social worlds is likely to have access to a wider range of information. It is better for individual success to have connections to a variety of networks rather than many connections within a single network. Similarly, individuals can exercise influence or act as brokers within their social networks by bridging two networks that are not directly linked essentially filling structural holes [1]. Resulting graphs from node/tie diagrams can be complex. Social Networks operate on many different levels from families up to nations, and play a critical role in determining the way problems are solved, organisations are run and the degree in which people succeed in achieving their goals. Below is an example of a social network diagram, the node with the highest betweenness centrality (Betweenness— The extent to which a node lies between other nodes in the network. This measure takes into account the connectivity of the node’s neighbours, giving a higher value for nodes which bridge clusters. The measure reflects the number of people who a person is connecting indirectly through their direct links, and Centrality—measure Social Networking Analysis 369 giving a rough indication of the social power of a node based on how well they “connect” the network) is marked in yellow [11]. A few analytic tendencies distinguish social network analysis. There is no assump- tion that groups are the building blocks of society: the approach is open to studying less-bounded social systems, from nonlocal communities to links among websites. Rather than treating individuals (persons, organizations, states) as discrete units of analysis, it focuses on how the structure of ties affects individuals and their relation- ships. In contrast to analyses that assume that socialization into norms determines behaviour, network analysis looks to see the extent to which the structure and com- position of ties affect norms. In fact, long before it became the commercialised and significant entertainment juggernaut that it is today, social networking was nothing more than a theory. How- ever, this theory of social networking stems back as far as the late 1800s as numer- ous sociologists were able to outline its basic principles [6]. German sociologist, Ferdinand Tönnies was a major contributor to sociological theory and it was him who initially highlighted that social groups exist by containing individuals which are linked together through shared beliefs and values. By the turn of the twentieth century, another major German sociologist, Georg Simmel became the first scholar to think appropriately in social network terms. Simmel produced a series of essays that pinpointed the nature of network size. He further displayed an understanding of social networking with his writings as he highlighted that social interaction existed within loosely-knit networks as opposed to groups [9]. The next real significant growth of social networking didn’t really commence until the 1930s when three main social networking traditions emerged. The first tradition to emerge was pioneered by Jacob Levy Moreno, who was recognised as one of the leading social scientists. Moreno began the systematic recording and analysis of social interaction in smaller groups such as work groups and classrooms. The second tradition was founded by a Harvard group which began to focus specifically on interpersonal relations at work. The third tradition originated from Alfred Radcliffe-Brown, an English social anthropologist. Radcliffe-Brown strongly urged the systematic studies of networks; ‘Social Network Analysis’ was born. However, SNA did not advance further until the 1950s. This was when social network analysis was developed through the kinship studies of Elizabeth Bott who studied at the University of Manchester in England. It was here that the University’s group of anthropologists began a series of investigations of community networks in regions such as Africa and India [11]. This research set the trend as more universities began similar investigations and studies as time progressed. During the 1960s a group of students at Harvard University began work to unite the different tracks and traditions already associated with social networking. Additional research was carried out in universities such as the University of California, Irvine and the University of Toronto. The latter contained a sociology group that emerged in the 1970s. The research undertook by this group argued that viewing the world in terms of social networks provided a greater analytical advantage. This view is also supported by Wasserman, S. and K. Faust, 1994, in their Social Network Analysis writings in the Cambridge University Press as they explain the extent of which SNA provides analytical advantage; “The unit of analysis in network analysis is not the individual, 370 K. Curran and N. Curran but an entity consisting of a collection of individuals and the linkages among them”. In recent times, social networking theories have been put aside as social networking has transferred to social media such as social networking sites like Facebook and MySpace. Although nowadays social networking is seen as more of an entertainment package, its roots stem back to the theoretical studies of sociologists such as Tönnies and Simmel as well as the progression of Social Network Analysis [7]. 2 Social Networking Social groups can exist as personal and direct social ties that either link individuals who share values and beliefs or impersonal, formal, and instrumental social links. Durkheim gave a non-individualistic explanation of social facts arguing that social phenomena arise when interacting individuals constitute a reality that can no longer be accounted for in terms of the properties of individual actors. He distinguished between a traditional society—“mechanical solidarity”—which succeeds if individ- ual differences are lessened, and the modern society that develops out of support between differentiated individuals with independent roles. Social network analysis has emerged as a key technique in modern sociology, and has also gained a following in anthropology; biology, communication studies, economics, geography, informa- tion science, organizational studies, social psychology, and sociolinguistics, and has become a popular topic of speculation and study. • Anthropology—is the study of humanity. It has origins in the natural sciences, the humanities, and the social sciences. • Biology—is a natural science concerned with the study of life and living organ- isms, including their structure, function, growth, origin, evolution, distribution, and taxonomy. • Communication Studies—is an academic field that deals with processes of com- munication, commonly defined as the sharing of symbols over distances in space and time.