Social Network Analysis – SNA


The Social Network Analysis (SNA) is a research procedure that focuses on identifying and comparing the relationships within and between individuals, groups and systems in order to model the real world interactions at the heart of organizational knowledge and learning processes. Essentially, Social Network Analysis aims at illuminating informal relationships: ‘who knows whom’ and ‘who shares with whom’. This allows researchers to visualize and understand the diverse relationships that either facilitate or impede knowledge sharing.


The study of networks has quite old historical roots. Both network studies and “graph theory” which has an important role in the analysis of network structures owe their birth and initial development to a famous riddle. In 1736, Leonhard Euler who was an important mathematician became interested in a mathematical riddle called the “Königsberg Bridge Problem”. The city of Königsberg which is called Kaliningrad today and lies in Russia, was built on the banks of the Pregel River in that was then Prussia and on two islands that lie in midstream. There were seven bridges in Pregel River that connect the land masses. The question that has become quite popular in that time asked “Does there exist any single path that crosses all seven bridges exactly once each?”. So the problem is, by starting from the islands or any of the land masses in the shore, to pass each of these seven bridges only once without moving or flying around the terrestrial and to be able to come back to the starting point. According to the rumors, the people of Königsberg have spent fruitless hours to find whether such a path exists. Euler proved that there is not, by observing that since any such path must both enter and leave every vertex it passes through, except the first and last, there can at most be two vertices in the network with an odd number of edges attached. Euler formed the basis of “graph theory” by putting forth of the properties of the graphs which is today called “Eulerian Graph” while searching for the solution of that riddle. Euler proved the impossibility of this path’s existence by using a graph which is a mathematical object consisting of points, also called vertices or nodes; and lines, also called edges or links. Thus, this famous bridge problem has become a mathematical expression as the question of whether there exists any “Eulerian Path” on the network. An Eulerian path is precisely a path that traverses each edge exactly once. Many consider Euler’s proof to be the first theorem of graph theory which has become the principal mathematical language for describing the properties of networks and is now highly developed field of mathematics (Ceyhun, 1976: 78, Barabasi, 2006: 1-2).

In its simplest form, a network consists of a set of discrete elements (vertices) and a set of connections (edges) that link the elements. These elements and their links can consist of many examples as computer and communication lines, people and their friendships or scientific publications and their citations and so on. This indicates the wide range usage area and power of graph theory. As a result, especially within the last decades, graph theory diverged from just being a mathematical theory and started to apply in other disciplines as computer sciences and engineering, but especially it gained a wide acceptance in sociology. (Kocak 2014: 1-2)


Social network analysis has a long history and connection to the study of organizations and businesses. Early social network research was built on manually collected and analyzed data about social ties. Since 1950’s, there has been an increasing interest for quantitative methods in sociology and anthropology, thus social scientists started to interest in mathematical language of graph theory in terms of examining the data obtained from ethnographic studies. A large part of the terminology that used in social network analysis has taken or adapted directly from graph theory. In similar, the structural properties and links of networks provide a useful tool for explaining the diffusion and impacts as well, like a possible diffusion of an epidemic or a global information transfer. Social network can be defined as a set of people -actor-, and the links and interactions between these actors. Nodes are the individual actors in a network; links are the relations between these actors. On the other hand, social network analysis can be expressed as examining the structure of social networks with the concepts of graph theory. In the center of network analysis, there are some key concepts which are fundamental for the discussion of social network. Some of these concepts are actor, relational tie, dyad, triad and subgroup. The social entities are referred as the concept of “actor”. These actors can be discrete individual, corporate or collective social units. Individuals in a group, departments within a corporate or nation-states in the world system can be the examples of the concept of “actor”. Most of social network applications focus on the same type of actor collections as people in a work group. These kinds of collections are called as one-mode network. Actors are linked to one another by social ties which can be handled as relational tie. A tie establishes a linkage between a pair of actors. The most common examples of ties can be expressed as behavioral interactions like talking together-sending messages, biological relationships like kinship, evaluation of one person by another like expressed friendship, liking, respect and transfers of material resources like business transactions etc. A relationship establishes a tie between two actors at the most basic level. So this tie is a property of the pair and it cannot be handled as a property of just an individual actor. Hence, a dyad consists of a pair of actors and the ties between them. Dyads are defined as the most basic units in the statistical analysis of social networks. On the other a triad is defined as a subset of three actors and the ties among them. A subgroup which is another concept in social network is defined as any subset of actors and all ties among them (Wasserman and Faust, 1994:17-19).


Internet and web are defined as a huge network which consist of connected computers, connected web sites or connected users (Scharnhorst, 2003). Therefore, the new developments in Internet caused the online restructuring of a huge social network and the properties of this new structure became the field of interest of many researchers. The rapidly growing popularity of social networks has let the sociologists and computer scientists to examine the properties of these networks. Based on previous knowledge it can be said that online social networks are consist of the actors and the links between these actors just like the other social networks. So, online social networks can also be analyzed by using the methods and concepts in graph theory and social network analysis.


A quick look at Social Network Analysis

The Social Network Analysis involves:

·        Collecting information about relationships within a defined group or network of people.

 – Identifying the target network (e.g. team, group, department).

 – Collecting data by interviewing managers and key players regarding specific needs and problems.

 – Outlining and clarifying objectives and the scope of analysis

 – Determining the level of reporting required.

 – Formulating hypotheses and questions.

– Developing a survey methodology and the questionnaire.

– Interviewing individuals in the network to identify relationships and knowledge flows.

·        Mapping out the network visually: mapping responses either manually or by using a software tool designed for the purpose.

·        Generating a baseline through the analysis of data from the survey responses.

·        Using this baseline for planning and prioritizing changes and interventions to improve social connections and knowledge flows within the group or network.

·        Designing and implementing actions to bring about

·        Mapping the network again after an appropriate period


Why Social Network Analysis?


In general, the popularity and the importance of social networks are increasing continuously because of the developments in information technologies’ which extensively moves every day’s life. In this context, to put forward all of the structural features of a social networks by using methods of social network analysis gain importance in terms of being able to create better understanding about a networks.

“The social network analysis means to analyze a social network by using the concepts of graph theory – concepts as degree, component, clique, path, etc. which are used to examine graph structures find their natural equivalents in social networks as well and they transform social network analysis to an objective method. It is seen that concepts of graph theory as degree distribution or the largest connected component which gradually became more refined are successfully applied to even quite large networks as Facebook, etc.” (Kocak 2014, 134)

At the conclusion of this brief blog covering the topic of Social Network Analysis it will be easy to figure out that value of comprehensive Social Network Analysis is substantially increasing in future. There are no estimates available covering period from now to forthcoming decades up to year 2040, however experts agree that by then, use of social media will be omnipresent and integrated into our daily lives in many ways. In this scenario challenge will be how to manage with the massive amounts of data what will overwhelm the masses.


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