# degree: Degree of the vertices In influential: Identification and Classification of the Most Influential Nodes

 degree R Documentation

## Degree of the vertices

### Description

This function and all of its descriptions have been obtained from the igraph package.

### Usage

``````degree(
graph,
v = V(graph),
mode = c("all", "out", "in", "total"),
loops = TRUE,
normalized = FALSE
)
``````

### Arguments

 `graph` The graph to analyze (an igraph graph). `v` The ids of vertices of which the degree will be calculated. `mode` Character string, “out” for out-degree, “in” for in-degree or “total” for the sum of the two. For undirected graphs this argument is ignored. “all” is a synonym of “total”. `loops` Logical; whether the loop edges are also counted. If the graph has a weight edge attribute, then this is used by default. Weights are used to calculate weighted shortest paths, so they are interpreted as distances. `normalized` Logical scalar, whether to normalize the degree. If TRUE then the result is divided by n-1, where n is the number of vertices in the graph.

### Value

A numeric vector of the same length as argument v.

`ivi`, `cent_network.vis`, and `degree` for a complete description on this function

Other centrality functions: `betweenness()`, `clusterRank()`, `collective.influence()`, `h_index()`, `lh_index()`, `neighborhood.connectivity()`, `sirir()`

### Examples

``````## Not run:
MyData <- coexpression.data
My_graph <- graph_from_data_frame(MyData)
GraphVertices <- V(My_graph)
My_graph_degree <- degree(My_graph, v = GraphVertices, normalized = FALSE)

## End(Not run)
``````

influential documentation built on Nov. 19, 2023, 9:06 a.m.