Social network analysis is a research technique that was primarily developed in the fields of sociology and communication science. It focuses on the patterns of relationships between individuals and between groups like states and organizations. The Web can host social networks because it links people and organizations. To study Web links, social network analysis has been employ. The Zapatista movement, a modern social movement in which the Internet played a key role, was review by Garrido and Halavais.
The study gathered information on links to the Zapatista website and organize these links into an online Zapatista network. This Web of websites offer a singular perspective on the nature of the Zapatistas’ extraordinary success. Barnett, Park, and the affiliation between the 152 most visited Web sites in Korea was examine using interdomain hypertext links. They then use cluster analysis to reveal a hyperlink network, and it was discover that financial Web sites occupied the center of the network.
The “small-world” theory, which has its roots in social network analysis research from more than 30 years ago, discusses the proximity of two randomly chosen people through intermediary chains of acquaintances. The theory has been apply to the web environment, where the number of links along directional link paths between two Web sites or Web pages has replace the number of intermediate acquaintances between two individuals. A tiny percentage of connections are require in a “small-world” network, like the Web, to serve as “shortcuts” connecting “distant” areas of the network. Numerous studies have been carried out.
Diagramming techniques are use to conduct social network analysis; these techniques do vary slightly depending on the specific study (Rice & Anderson, 1994; Anderson, 2002): They are all refer to as networks, with the actors (such as people, professions, departments, or projects) acting as the knots and the connections between the knots being name arrows. For example, relationships could be of communication, competence, or economic variety. Numerous characteristics, such as frequency, relationship type, interaction level, or intensity, describe the relationships. The collect data are then examine using various methods that highlight the relationships.
In SNA, networks of people are visualize as graphs, which are then explore. Typically, nodes represent people in a social network, and edges between nodes represent one or more relationships between them (Figure 14.2). The resulting graph can show how people are connect. Small networks can be visualize, and these visual representations are intuitive, can reveal patterns of connections, and can highlight nodes that are highly connect or crucial for uniting groups. It becomes necessary to use graph analytic techniques to compute the properties of the nodes, and the graph as a whole as the network representation of a community expands.
Techniques for SNA that use graph analysis are generally focus on connections, distributions, and clustering. Let us start by looking at a social network’s analysis of connections. The SNA contains some terms unique to social (human) relationship networks. However, many SNA techniques are the same as those used in other kinds of networks. Here are four terms from SNA that have to do with connections: propinquity, reciprocity, multiplexity, and homophily. Homophily is meant by the proverb “birds of a feather flock together.” It refers to the propensity for people to bond with others with whom they share a trait. These traits can be as straightforward as race, gender, or age or less obvious, like educational attainment, interests, or religious convictions.
Homophily is a helpful way to explore the idea of agency because it allows people to act differently from what is expect, forming bonds between groups that might not otherwise interact in any way other than through homophily. The term “multiplexity” describes the potential for various relationships to develop between two individuals. A graph exhibiting this property is generally refer to as a multi-partite graph. Relationship directionality is implied by reciprocity. One edge that points at both nodes can represent a reciprocal relationship, while two edges can represent a bidirectional relationship. As a result, a social network that depicts node reciprocity is, by definition, a directed graph.
SNA’s origins are multifaceted. In the social sciences, network theory has its roots in Georg Simmel’s work from the final decade of the 20th century (Simmel, 1908/2009). Sociometry, the forerunner of SNA, started with Moreno’s network visualizations, which could show up to 435 people (Moreno, 1934). Three disciplines, namely social psychology, sociology, and social anthropology. It have been particularly interest in representing social relations by graphs of points and lines. Cartwright and Harary’s research on more complex instances of structural balancing was inspire by Heider’s balance theory. It sought to describe the “equilibrium” characteristics of interpersonal relations (i.e., groups with more than three elements).