从数据框中的二进制和字符变量创建双模式网络
Creating two-mode network from binary and character variables in data frame
SNA 人员：我正在尝试从 R 中的数据框创建双模式网络。我有一个组织列表，这些组织通过父组织中的共同成员资格连接。我在那个用二进制变量编码的组织中有成员资格。我已经通过以下代码（来自 ）基于这些数据成功创建了社会矩阵和后续网络对象：
library(statnet)
org <- c("A","B","C","D","E","F","G","H","I","J")
link <- c(1,0,0,0,1,1,0,0,1,1)
person <- c("Mary","Michael","Mary","Jane","Jimmy",
"Johnny","Becky","Bobby","Becky","Becky")
df <- data.frame(org,link,person)
socmat1 <- tcrossprod(df$link)
rownames(socmat1) <- df$org
colnames(socmat1) <- df$org
diag(socmat1) <- 0
socmat1
#> A B C D E F G H I J
#> A 0 0 0 0 1 1 0 0 1 1
#> B 0 0 0 0 0 0 0 0 0 0
#> C 0 0 0 0 0 0 0 0 0 0
#> D 0 0 0 0 0 0 0 0 0 0
#> E 1 0 0 0 0 1 0 0 1 1
#> F 1 0 0 0 1 0 0 0 1 1
#> G 0 0 0 0 0 0 0 0 0 0
#> H 0 0 0 0 0 0 0 0 0 0
#> I 1 0 0 0 1 1 0 0 0 1
#> J 1 0 0 0 1 1 0 0 1 0
testnet <- as.network(x = socmat1,
directed = FALSE,
loops = FALSE,
matrix.type = "adjacency"
)
testnet
#> Network attributes:
#> vertices = 10
#> directed = FALSE
#> hyper = FALSE
#> loops = FALSE
#> multiple = FALSE
#> bipartite = FALSE
#> total edges= 10
#> missing edges= 0
#> non-missing edges= 10
#>
#> Vertex attribute names:
#> vertex.names
#>
#> No edge attributes
由 reprex package (v0.3.0)
于 2020-10-24 创建
但是，我显然不能类似地使用tcrossprod()来实现与组织连接的个人相同的结果，反之亦然，如下代码所示：
socmat2 <- tcrossprod(df$org)
#> Error in df$org: object of type 'closure' is not subsettable
rownames(socmat2) <- df$person
#> Error in df$person: object of type 'closure' is not subsettable
colnames(socmat2) <- df$person
#> Error in df$person: object of type 'closure' is not subsettable
diag(socmat2) <- 0
#> Error in diag(socmat2) <- 0: object 'socmat2' not found
socmat2
#> Error in eval(expr, envir, enclos): object 'socmat2' not found
如何创建双模式网络，第一组边是组织在较大组织中的成员资格（由 link 变量表示），第二组边是个人在组织中的领导职位？
谢谢大家。
由 reprex package (v0.3.0)
于 2020-10-24 创建
有许多不同的方法可以完成您想要做的事情。我不知道有什么函数可以根据您拥有的数据神奇地创建 two-mode 网络，因此下面的解决方案涉及一些数据操作。我们首先创建一个带有节点的数据框，然后是另一个带有边的数据框。然后使用节点和边作为输入来创建一个 network 对象。代码是self-explanatory:
library(tidyverse)
library(network)
# Let's create a 'nodes' data frame
my_nodes <- as.data.frame(rbind(
cbind(nodename = org, type = "Organization"),
cbind(unique(person), "People"),
cbind("Parent", "Parent org")))
# Let's add an ID column to the nodes data frame
my_nodes <- rowid_to_column(my_nodes, "ID")
# Let's create a data frame with al possible edges
# (i.e., connecting organizations to people and organizations to the parent organization)
my_edges <- data.frame(rbind(
cbind(ColA = org, ColB = person, type = "Set 1"),
cbind(org, link, "Set 2")))
my_edges <- subset(my_edges, ColB != 0)
my_edges$ColB[my_edges$ColB == 1] <- "Parent"
# Let's set up the network object using edges and nodes
my_network <- network(my_edges,
vertex.attr = my_nodes,
matrix.type = "edgelist",
ignore.eval = FALSE)
请注意，我们创建了一个列 type 来对节点和边进行分类。我们可以在可视化网络时使用type来改变node/edge颜色、大小、形状等。
这里是一个使用包 igraph 的例子。首先，我们将 network 对象转换为 igraph 对象。
library(igraph)
library(intergraph)
my_netgraph <- asIgraph(my_network)
可以使用 V(my_netgraph)$attribute_name 评估节点的属性。例如，让我们看一下我们之前定义的网络中的 type 个节点：
> V(my_netgraph)$type
[1] "Organization" "Organization" "Organization" "Organization" "Organization" "Organization"
[7] "Organization" "Organization" "Organization" "Organization" "People" "People"
[13] "People" "People" "People" "People" "People" "Parent org"
现在让我们根据 type 为这些节点着色。为此，我们将创建一个新属性 $color。每个$color应该对应不同的$type:
V(my_netgraph)[V(my_netgraph)$type == "People"]$color <- "green"
V(my_netgraph)[V(my_netgraph)$type == "Organization"]$color <- "red"
V(my_netgraph)[V(my_netgraph)$type == "Parent org"]$color <- "yellow"
plot(my_netgraph)
这是网络现在的样子：
现在让我们根据属性 $type 更改节点的 $shape:
V(my_netgraph)[V(my_netgraph)$type == "People"]$shape <- "circle"
V(my_netgraph)[V(my_netgraph)$type == "Organization"]$shape <- "square"
V(my_netgraph)[V(my_netgraph)$type == "Parent org"]$shape <- "rectangle"
plot(my_netgraph)
我们可以使用以下函数更改 igraph 对象的其他属性：
E(my_netgraph) # changes he edges of the "net" object
V(my_netgraph) # changes the vertices of the "net" object
E(my_netgraph)$type # changes edge attribute "type"
V(my_netgraph)$media # changes the vertex attribute "media"
您可以在 this iGraph manual（第 10-11 页）上找到更多详细信息。
SNA 人员：我正在尝试从 R 中的数据框创建双模式网络。我有一个组织列表，这些组织通过父组织中的共同成员资格连接。我在那个用二进制变量编码的组织中有成员资格。我已经通过以下代码（来自
library(statnet)
org <- c("A","B","C","D","E","F","G","H","I","J")
link <- c(1,0,0,0,1,1,0,0,1,1)
person <- c("Mary","Michael","Mary","Jane","Jimmy",
"Johnny","Becky","Bobby","Becky","Becky")
df <- data.frame(org,link,person)
socmat1 <- tcrossprod(df$link)
rownames(socmat1) <- df$org
colnames(socmat1) <- df$org
diag(socmat1) <- 0
socmat1
#> A B C D E F G H I J
#> A 0 0 0 0 1 1 0 0 1 1
#> B 0 0 0 0 0 0 0 0 0 0
#> C 0 0 0 0 0 0 0 0 0 0
#> D 0 0 0 0 0 0 0 0 0 0
#> E 1 0 0 0 0 1 0 0 1 1
#> F 1 0 0 0 1 0 0 0 1 1
#> G 0 0 0 0 0 0 0 0 0 0
#> H 0 0 0 0 0 0 0 0 0 0
#> I 1 0 0 0 1 1 0 0 0 1
#> J 1 0 0 0 1 1 0 0 1 0
testnet <- as.network(x = socmat1,
directed = FALSE,
loops = FALSE,
matrix.type = "adjacency"
)
testnet
#> Network attributes:
#> vertices = 10
#> directed = FALSE
#> hyper = FALSE
#> loops = FALSE
#> multiple = FALSE
#> bipartite = FALSE
#> total edges= 10
#> missing edges= 0
#> non-missing edges= 10
#>
#> Vertex attribute names:
#> vertex.names
#>
#> No edge attributes
由 reprex package (v0.3.0)
于 2020-10-24 创建但是，我显然不能类似地使用tcrossprod()来实现与组织连接的个人相同的结果，反之亦然，如下代码所示：
socmat2 <- tcrossprod(df$org)
#> Error in df$org: object of type 'closure' is not subsettable
rownames(socmat2) <- df$person
#> Error in df$person: object of type 'closure' is not subsettable
colnames(socmat2) <- df$person
#> Error in df$person: object of type 'closure' is not subsettable
diag(socmat2) <- 0
#> Error in diag(socmat2) <- 0: object 'socmat2' not found
socmat2
#> Error in eval(expr, envir, enclos): object 'socmat2' not found
如何创建双模式网络，第一组边是组织在较大组织中的成员资格（由 link 变量表示），第二组边是个人在组织中的领导职位？
谢谢大家。
由 reprex package (v0.3.0)
于 2020-10-24 创建有许多不同的方法可以完成您想要做的事情。我不知道有什么函数可以根据您拥有的数据神奇地创建 two-mode 网络，因此下面的解决方案涉及一些数据操作。我们首先创建一个带有节点的数据框，然后是另一个带有边的数据框。然后使用节点和边作为输入来创建一个 network 对象。代码是self-explanatory:
library(tidyverse)
library(network)
# Let's create a 'nodes' data frame
my_nodes <- as.data.frame(rbind(
cbind(nodename = org, type = "Organization"),
cbind(unique(person), "People"),
cbind("Parent", "Parent org")))
# Let's add an ID column to the nodes data frame
my_nodes <- rowid_to_column(my_nodes, "ID")
# Let's create a data frame with al possible edges
# (i.e., connecting organizations to people and organizations to the parent organization)
my_edges <- data.frame(rbind(
cbind(ColA = org, ColB = person, type = "Set 1"),
cbind(org, link, "Set 2")))
my_edges <- subset(my_edges, ColB != 0)
my_edges$ColB[my_edges$ColB == 1] <- "Parent"
# Let's set up the network object using edges and nodes
my_network <- network(my_edges,
vertex.attr = my_nodes,
matrix.type = "edgelist",
ignore.eval = FALSE)
请注意，我们创建了一个列 type 来对节点和边进行分类。我们可以在可视化网络时使用type来改变node/edge颜色、大小、形状等。
这里是一个使用包 igraph 的例子。首先，我们将 network 对象转换为 igraph 对象。
library(igraph)
library(intergraph)
my_netgraph <- asIgraph(my_network)
可以使用 V(my_netgraph)$attribute_name 评估节点的属性。例如，让我们看一下我们之前定义的网络中的 type 个节点：
> V(my_netgraph)$type
[1] "Organization" "Organization" "Organization" "Organization" "Organization" "Organization"
[7] "Organization" "Organization" "Organization" "Organization" "People" "People"
[13] "People" "People" "People" "People" "People" "Parent org"
现在让我们根据 type 为这些节点着色。为此，我们将创建一个新属性 $color。每个$color应该对应不同的$type:
V(my_netgraph)[V(my_netgraph)$type == "People"]$color <- "green"
V(my_netgraph)[V(my_netgraph)$type == "Organization"]$color <- "red"
V(my_netgraph)[V(my_netgraph)$type == "Parent org"]$color <- "yellow"
plot(my_netgraph)
这是网络现在的样子：
现在让我们根据属性 $type 更改节点的 $shape:
V(my_netgraph)[V(my_netgraph)$type == "People"]$shape <- "circle"
V(my_netgraph)[V(my_netgraph)$type == "Organization"]$shape <- "square"
V(my_netgraph)[V(my_netgraph)$type == "Parent org"]$shape <- "rectangle"
plot(my_netgraph)
我们可以使用以下函数更改 igraph 对象的其他属性：
E(my_netgraph) # changes he edges of the "net" object
V(my_netgraph) # changes the vertices of the "net" object
E(my_netgraph)$type # changes edge attribute "type"
V(my_netgraph)$media # changes the vertex attribute "media"
您可以在 this iGraph manual（第 10-11 页）上找到更多详细信息。