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**Node:** in mathematical terms, each object in a social network graph is called a node. In sociological terms, each node can also be called an **actor**.

**Edge:** in mathematical terms, the line linking more than one node is called an edge.

**Tie:** the edge between two nodes can also be called a tie. Ties can be directed or undirected. Most of the social network analysis case studies we have undertaken feature **undirected ties**; the relationship between the two actors is the same in both directions. Directed ties exhibit 'directionality', meaning that the relationship between the individuals is uneven. Grantor and beneficiary analysis involves **directed ties**, because there is the gift is moving from the grantor to the beneficiary.

**Sociogram:** graphs in SNA are known as sociograms.

**Dyad:** A pair of two actors in a sociogram.

**Triad:** A group of three actors in a sociogram. The theory of dyads and triads predates social network analysis, going back to the work of sociologist Georg Simmel (1858-1918).

**Clique**: three or more actors who are all connected directly to each other

**Centrality**: ‘importance’ (often suggesting influence, leadership, or flow of information) of a person in a sociogram (social network graph)

**Degree centrality**: how many people a single actor is connected to; number of contacts a person has in his/her network

**Eigenvector centrality**: a refinement of degree centrality which weighs the importance of the contacts in one’s network according to *their *degrees. Tells us not just how many people an actor is connected to, but also how many important people an actor was connected to.

**Betweenness centrality**: a form of centrality that focuses on the place of an actor within a network structure. This is calculated by looking at how many times an actor sits on the shortest path (called the 'geodesic') linking two other actors. A characteristic example of a person with high betweenness centrality is William del Bois, chancellor (d. 1232). In this sociogram of actors witnessing together more than twenty times, he occupies a pivotal position.

**Closeness centrality: **a form of centrality that emphasizes the independence of an actor. Being close to many other actors means that a particular actor will not have to rely on intermediaries, and is better placed to be a mobilizing force. In that sense, closeness is something of a corollary to betweenness. Closeness centrality is measured using a concept called distance. **Distance** in a sociogram is the length of the shortest path between two nodes.

**Ego-network: **a network defined as all the contacts of a single actor. In other words, the network is composed only of the defining actor (‘ego’) and those to whom he/she is directly connected (‘alters’). The ego-network emphasises the extent to which those alters are connected also to each other. ‘How many of ego’s friends know each other?’

**Ego-network size:** because the ego-network is defined as all the people connected to ego, the ‘size’ of the ego-network (number of ‘alters’) will always be the same as ego’s degree centrality.

**Ego-network density**: perhaps best thought of as ‘connectedness’, or the extent to which all the actors in the network are interconnected. Density is expressed as a fraction or a percentage, in terms of how many potential ties are actually present. An ego-network density of 1 (or 100%) means that all the people in the graph are connected to each other. A low density means that most of the contacts of ego are not also connected to each other, or that many of ego’s friends and acquaintances do not know each other.

**Theory terms:**

Closure:

Diffusion:

Homophily:

Structural holes:

Weak ties: