"A component is a subgraph in which all points are directly or indirectly connected to each other and there are no connec-tions to points outside the subgraph. Information or resources can, therefore, flow along a path through all the members of the component but cannot reach any other points in the graph. A graph may comprise one or more components of varying size, and the number and size distribution of components is a fundamental measure of network differentiation and of the existence of boundaries to the flow of information and resources." (John Scott," What is Social Network Analysis?", 2012)
"A final measure of centrality is one that measures the extent to which a point is able to act as an intermediary in a large number of network flows. This measure has been called ‘betweenness’ and refers to the extent to which a particular point is able to serve as an intermediate point of contact between any two other points." (John Scott," What is Social Network Analysis?", 2012)
"A further refinement of the simple component idea is that of the cyclic component built from intersecting cycles of connection. A cycle is a directed path that returns to its starting point. The overlapping of such cycles produces a cyclic compo-nent in which all points are connected by one or more cycles and no points have cyclic connections outside the component. A cyclic component is a structural element within a strong component and may be connected to other members of the strong component through ‘bridges’ that do not lie on the cycle itself." (John Scott," What is Social Network Analysis?", 2012)
"A further measure of global cohesion is the centralisation of a network. Where centrality relates to the position of particular points, centralisation relates to the overall structure of a network. Centralisation measures the extent to which the cohesion of a network is organised around a specific point or set of connected points. The spokes on a bicycle wheel, for example, form a highly centralised network around its hub. Measures of centralisation can be based on the degree, distance, or betweenness of points, and extensions of these concepts have involved the idea that it is possible to identify the sets of points that comprise the centre, margin, and periphery of the network as a whole." (John Scott," What is Social Network Analysis?", 2012)
"A whole collection of global measures cluster around the idea of the centrality of points within their graphs. The degree of a point - its total of incoming and outgoing lines - is the most basic measure and has been termed local centrality. Calculating the degrees of all points in a network and ranking them from highest to lowest gives a rank order of local centrality. This centrality is ‘local’ because it highlights points that are well-connected in their immediate neighbourhoods. Such points may not, however, be central in the more global sense that a circle or sphere has a unique centre that can be understood in quasi-spatial terms. Locally central points are well-connected within particular parts of the network but may not be at all well-connected in a global sense." (John Scott," What is Social Network Analysis?", 2012)
"Inclusiveness simply measures the number or proportion of the whole set of points that are actually connected into one or more parts of the graph. Some points may be isolates, having no ties to other points, while others will be connected, to a greater or lesser extent, into larger structures. The inclusiveness of a graph is simply the total number of non-isolated points, gener-ally expressed as a percentage of the total number of points. Inclusiveness is a rough and ready approximation to cohesion, but it is usually more informative to measure the actual density of the graph." (John Scott," What is Social Network Analysis?", 2012)
"Social network analysis conceptualises individuals or groups as ‘points’ and their relations to each other as ‘lines’. It is concerned with the patterns formed by the points and lines and involves exploring these patterns, mathematically or visually, in order to assess their effects on the individuals and organisations that are the members of the ‘networks’ formed by the intersecting lines that connect them. It therefore takes the metaphorical idea of interaction as forming a network of connections and gives this idea a more formal representation in order to model structures of social relations. Treating a social structure as a network is the cornerstone of social network analysis." (John Scott," What is Social Network Analysis?", 2012)
"The converse of centrality is peripherality and it can be useful to know those points that are least close to other members of their networks. Such points are not isolated but are poorly integrated into their network. They are likely to have little influ-ence and to be uninvolved in significant communication flows through the network." (John Scott," What is Social Network Analysis?", 2012)
"The density of a graph is a very useful and direct measure of its cohesion, but it has one major limitation as a comparative measure of social structure. In real situations, density varies with the size of a network and this limits the possibilities of using the measure to compare different types of network. It is highly unlikely that agents are able to sustain more than a certain number of relationships: our ability to be ‘friends’ with people, for example, has its limits." (John Scott," What is Social Network Analysis?", 2012)
"The sociometric uses of graph theory measured the ‘distance’ from one individual to another by the number of links that must be traversed to connect the two. This is a useful measure of closeness, but it does not correspond to the everyday idea of distance as something measured across a physical space. In a sociogram, the physical arrangement of points is arbitrary, limited only by the aesthetic attempt to minimise overlaps among the lines. A measure of physical distance, however, requires a non-arbitrary representation of the data." (John Scott," What is Social Network Analysis?", 2012)
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