Social Network Analysis Methodology

Social Network Analysis as Research Methodology

Social Network Analysis is an interdisciplinary research programme which helps in predicting the structures of relationships among social entities as well as impact of said structure on the other social phenomenon. The essential elements of this programme are built around some core concepts and methods for the measurement, representation and analysis of social structure. A social network is a set of actors (points, nodes or agents) that may have relationships (or ties) with one another. A network can have one or more actors and there can be one or more kinds of relations between pair of actors. Scientists in the social network field use specialized jargon and notation. Much of this is borrowed

The first true formulation of social network analysis was taken seriously in the American social psychology of the 1930s. Moreno developed ‘sociometry’ and drew ‘sociograms’ as a method in which lines between points represented the friendship choices made by the people represented by the points. Social Network Analysis started with a desire to know more about the properties of the networks of social relations. It offered a new way of looking at the old problems and a different perspective for forming powerful theoretical concepts.

Characteristics of Social Network Analysis

1. Social network analysis is an approach that allows researchers to document, represent, and analyze the impact of relationship patterns.

2. The Communication Infrastructure approach is based on understanding how networks of residents, organizations, and media in the community interact.

3. Dependence on secondary data (like publicly available records) or primary data (where you collect your own information about connections) to conduct this analysis.

4. Network analysis looks at the relationship between two basic components - nodes (people, organizations, documents) and ties (relationships, affiliations,

The actors are not sampled individually, for example if we want to look at the relationship ties of ‘A’ with suppose five friends, then we also have to look at the relationship ties of the five friends. So the sample now consists of ‘A’ plus all the five friends. So the sample elements are no longer independent. The actors included in non-network studies tend to be the result of independent probability sampling. Most of the time, network studies don’t use samples, rather the whole population is studied. The use of whole populations as a way of selecting observations in (many) network studies makes it important for the analyst to be clear about the boundaries of each population to be studied, and how individual units of observation are to be selected within that population. Network data sets also frequently involve several levels of analysis, with actors embedded at the lowest