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vcount(G)
net <- networkPlot(adjmt, cluster="louvain", n=vcount(G), type="kamada")
View(adjmt)
View(adjmt)
G <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="undirect")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, cluster="louvain", n=vcount(G), type="kamada")
net2VOSviewer(net, vos.path = "VOS")
net <- networkPlot(adjmt, cluster="louvain", n=vcount(G), type="kamada")
library(readxl)
library(quanteda)
library(igraph)
library(bibliometrix)
library(CINNA)
comment_nlp <- read_excel("./source/comment_cooc_assoc.xlsx")
rn1 <- as.matrix(comment_nlp[,1])
comment_nlp <- comment_nlp[2:497]
row.names(comment_nlp) <- rn1
adjmt <- as.matrix(comment_nlp)
total_occurrences <- colSums(adjmt)
G <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="undirect")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, cluster="louvain", n=vcount(G), type="kamada")
library(readxl)
library(quanteda)
library(igraph)
library(bibliometrix)
library(CINNA)
comment_nlp <- read_excel("./source/comment_cooc_assoc.xlsx")
rn1 <- as.matrix(comment_nlp[,1])
comment_nlp <- comment_nlp[2:497]
row.names(comment_nlp) <- rn1
adjmt <- as.matrix(comment_nlp)
total_occurrences <- colSums(adjmt)
G <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="undirect")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, cluster="louvain", n=vcount(G), type="kamada")
net2VOSviewer(net, vos.path = "VOS")
View(adjmt)
G <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="upper")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, cluster="louvain", n=vcount(G), type="kamada")
networkPlot(adjmt, cluster="louvain", n=vcount(G), type="kamada")
comment_nlp <- read_excel("./source/comment_cooc_jacc.xlsx")
rn1 <- as.matrix(comment_nlp[,1])
comment_nlp <- comment_nlp[2:497]
row.names(comment_nlp) <- rn1
adjmt <- as.matrix(comment_nlp)
total_occurrences <- colSums(adjmt)
G <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="upper")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, cluster="louvain", n=vcount(G), type="kamada")
comment_nlp <- read_excel("./source/comment_cooc_assoc.xlsx")
rn1 <- as.matrix(comment_nlp[,1])
comment_nlp <- comment_nlp[2:497]
row.names(comment_nlp) <- rn1
adjmt <- as.matrix(comment_nlp)
total_occurrences <- colSums(adjmt)
G <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="upper")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, cluster="louvain", n=vcount(G), type="kamada")
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
net <- networkPlot(adjmt, cluster="louvain", n=vcount(G), type="kamada")
plot(G, layout=layout_with_kk)
net <- networkPlot(adjmt, cluster="louvain", n=vcount(G), type="kamada")
net <- networkPlot(adjmt, cluster="louvain", type="kamada")
net <- networkPlot(adjmt, n=vcount(G), type="kamada")
View(adjmt)
dim(adjmt)
net <- networkPlot(adjmt, normalize=NULL, cluster="louvain", n=vcount(G), type="kamada")
net <- networkPlot(G, normalize=NULL, cluster="louvain", n=vcount(G), type="kamada")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, normalize=NULL, n=vcount(G), type="kamada")
library(readxl)
library(quanteda)
library(igraph)
library(bibliometrix)
library(CINNA)
comment_nlp <- read_excel("./source/comment_cooc_assoc.xlsx")
rn1 <- as.matrix(comment_nlp[,1])
comment_nlp <- comment_nlp[2:497]
row.names(comment_nlp) <- rn1
adjmt <- as.matrix(comment_nlp)
total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="upper")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, normalize=NULL, n=vcount(G1), type="kamada")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, normalize=NULL, n=vcount(G1), type="kamada")
comment_nlp <- read_excel("./source/comment_cooc_jacc.xlsx")
comment_nlp <- read_excel("./source/comment_cooc_assoc.xlsx")
comment_nlp <- read_excel("./source/comment_cooc_assoc.xlsx")
comment_nlp <- read_excel("./source/comment_cooc_assoc.xlsx")
library(readxl)
library(quanteda)
library(igraph)
library(bibliometrix)
library(CINNA)
comment_nlp <- read_excel("./source/comment_cooc_assoc.xlsx")
comment_nlp <- read_excel("./source/comment_cooc_jacc.xlsx")
library(readxl)
library(quanteda)
library(igraph)
library(bibliometrix)
library(CINNA)
comment_nlp <- read_excel("./source/comment_cooc_jacc.xlsx")
rn1 <- as.matrix(comment_nlp[,1])
comment_nlp <- comment_nlp[2:497]
row.names(comment_nlp) <- rn1
adjmt <- as.matrix(comment_nlp)
#total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="upper")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, normalize=NULL, n=vcount(G1), type="kamada")
comment_nlp <- read_excel("./source/comment_cooc_assoc.xlsx")
rn1 <- as.matrix(comment_nlp[,1])
comment_nlp <- comment_nlp[2:497]
row.names(comment_nlp) <- rn1
adjmt <- as.matrix(comment_nlp)
#total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="upper")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, normalize=NULL, n=vcount(G1), type="kamada")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, normalize=NULL, n=vcount(G1), type="kamada")
#total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="lower")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, normalize=NULL, n=vcount(G1), type="kamada")
dim(adjmt)
adjmt
vcount(G1)
networkPlot(adjmt, normalize=NULL, n=vcount(G1), type="kamada")
net <- networkPlot(adjmt, normalize="association", n=vcount(G1), type="kamada")
library(readxl)
library(quanteda)
library(igraph)
library(bibliometrix)
library(CINNA)
comment_nlp <- read_excel("./source/comment_cooc_assoc.xlsx")
rn1 <- as.matrix(comment_nlp[,1])
comment_nlp <- comment_nlp[2:497]
row.names(comment_nlp) <- rn1
adjmt <- as.matrix(comment_nlp)
#total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="lower")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, normalize="association", n=vcount(G1), type="kamada")
networkPlot(adjmt, normalize="association", n=vcount(G1), type="kamada")
net <- networkPlot(adjmt, n=vcount(G1), type="kamada")
View(adjmt)
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, n=vcount(G1), type="kamada")
comment_nlp <- read_excel("./source/comment_cooc_freq.xlsx")
rn1 <- as.matrix(comment_nlp[,1])
comment_nlp <- comment_nlp[2:497]
row.names(comment_nlp) <- rn1
adjmt <- as.matrix(comment_nlp)
#total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="lower")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, n=vcount(G1), type="kamada")
library(readxl)
library(quanteda)
library(igraph)
library(bibliometrix)
library(CINNA)
comment_nlp <- read_excel("./source/comment_cooc_assoc.xlsx")
rn1 <- as.matrix(comment_nlp[,1])
comment_nlp <- comment_nlp[2:497]
row.names(comment_nlp) <- rn1
adjmt <- as.matrix(comment_nlp)
#total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="lower")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, n=vcount(G1), type="kamada")
#total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="max")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, n=vcount(G1), type="kamada")
View(G1)
networkPlot(adjmt, n=vcount(G1), type="kamada")
E(G1)$weight
net <- networkPlot(adjmt, n=vcount(G1), type="kamada")
View(rn1)
library(readxl)
library(quanteda)
library(igraph)
library(bibliometrix)
library(CINNA)
comment_nlp <- read_excel("./source/comment_cooc_assoc.xlsx")
View(comment_nlp)
rn1 <- as.matrix(comment_nlp[,1])
comment_nlp <- comment_nlp[2:497]
row.names(comment_nlp) <- rn1
adjmt <- as.matrix(comment_nlp)
#total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="max")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, n=vcount(G1), type="kamada")
networkPlot(adjmt, n=vcount(G1), type="fruchterman")
View(adjmt)
View(comment_nlp)
networkPlot(comment_nlp, n=vcount(G1), type="fruchterman")
library(readxl)
library(quanteda)
library(igraph)
library(bibliometrix)
library(CINNA)
comment_nlp <- read_excel("./source/comment_cooc_assoc.xlsx")
rn1 <- as.matrix(comment_nlp[,1])
comment_nlp <- comment_nlp[2:497]
row.names(comment_nlp) <- rn1
adjmt <- as.data.frame(comment_nlp)
View(adjmt)
#total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="max")
par(mar=c(1,1,1,1))
net <- networkPlot(comment_nlp, n=vcount(G1), type="fruchterman")
adjmt <- as.matrix(comment_nlp)
#total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="max")
par(mar=c(1,1,1,1))
net <- networkPlot(comment_nlp, n=vcount(G1), type="fruchterman")
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
View(adjmt)
net <- networkPlot(adjmt, n=vcount(G1), type="kamada")
net <- networkPlot(adjmt, n=vcount(G1), type="kamada")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, n=vcount(G1), type="kamada")
net2VOSviewer(net, vos.path = "VOS")
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
library(readxl)
library(quanteda)
library(igraph)
library(bibliometrix)
library(CINNA)
comment_nlp <- read_excel("./source/comment_cooc_assoc.xlsx")
rn1 <- as.matrix(comment_nlp[,1])
#comment_nlp <- comment_nlp[2:497]
comment_nlp <- comment_nlp[2:24]
row.names(comment_nlp) <- rn1
adjmt <- as.matrix.data.frame(comment_nlp)
#total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="max")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, n=vcount(G1), type="kamada")
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
View(adjmt)
(
;
#total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="max")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, n=vcount(G1), type="kamada")
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
net <- networkPlot(adjmt, n=vcount(G1), type="kamada")
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
library(readxl)
library(quanteda)
library(igraph)
library(bibliometrix)
library(CINNA)
comment_nlp <- read_excel("./source/comment_cooc_assoc.xlsx")
rn1 <- as.matrix(comment_nlp[,1])
comment_nlp <- comment_nlp[2:497]
#comment_nlp <- comment_nlp[2:13]
row.names(comment_nlp) <- rn1
adjmt <- as.matrix.data.frame(comment_nlp)
#total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="lower")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, n=vcount(G1), type="kamada")
net2VOSviewer(net, vos.path = "VOS")
net2VOSviewer(net, vos.path = "VOS")
library(readxl)
library(quanteda)
library(igraph)
library(bibliometrix)
library(CINNA)
comment_nlp <- read_excel("./source/comment_cooc_assoc.xlsx")
rn1 <- as.matrix(comment_nlp[,1])
comment_nlp <- comment_nlp[2:497]
#comment_nlp <- comment_nlp[2:13]
row.names(comment_nlp) <- rn1
adjmt <- as.matrix.data.frame(comment_nlp)
#total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="lower")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, n=vcount(G1), type="kamada")
net2VOSviewer(net, vos.path = "VOS")
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
library(readxl)
library(quanteda)
library(igraph)
library(bibliometrix)
library(CINNA)
comment_nlp <- read_excel("./source/comment_cooc_jacc.xlsx")
rn1 <- as.matrix(comment_nlp[,1])
comment_nlp <- comment_nlp[2:497]
#comment_nlp <- comment_nlp[2:13]
row.names(comment_nlp) <- rn1
adjmt <- as.matrix.data.frame(comment_nlp)
#total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="lower")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, normalize="jaccard", n=vcount(G1), type="kamada")
net2VOSviewer(net, vos.path = "VOS")
net <- networkPlot(adjmt, normalize=NULL, n=vcount(G1), type="kamada")
library(igraph)
library(igraph)
library(bibliometrix)
data(scientometrics)
NetMatrix <- biblioNetwork(scientometrics, analysis = "co-occurrences",
network = "authors", sep = ";")
View(scientometrics)
networkPlot(NetMatrix, n=30, normalize = "association",labelsize=1)
View(NetMatrix)
library(readxl)
library(quanteda)
library(igraph)
library(bibliometrix)
library(CINNA)
comment_nlp <- read_excel("./source/comment_cooc_jacc.xlsx")
rn1 <- as.matrix(comment_nlp[,1])
comment_nlp <- comment_nlp[2:497]
#comment_nlp <- comment_nlp[2:13]
row.names(comment_nlp) <- rn1
adjmt <- as.matrix.data.frame(comment_nlp)
#total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="lower")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, normalize=NULL, n=vcount(G1), type="kamada")
net2VOSviewer(net, vos.path = "VOS")
library(readxl)
library(quanteda)
library(igraph)
library(bibliometrix)
library(CINNA)
comment_nlp <- read_excel("./source/comment_cooc_assoc.xlsx")
rn1 <- as.matrix(comment_nlp[,1])
comment_nlp <- comment_nlp[2:497]
#comment_nlp <- comment_nlp[2:13]
row.names(comment_nlp) <- rn1
adjmt <- as.matrix.data.frame(comment_nlp)
#total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="lower")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, normalize=NULL, n=vcount(G1), type="kamada")
plot(G, layout=layout_with_kk)
plot(G1, layout=layout_with_kk)
net <- networkPlot(adjmt, normalize=NULL, n=vcount(G1), type="kamada")
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
net2VOSviewer(net, vos.path = "VOS")
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
library(igraph)
library(bibliometrix)
data(scientometrics)
NetMatrix <- biblioNetwork(scientometrics, analysis = "co-occurrences",
network = "authors", sep = ";")
View(NetMatrix)
as.matrix(NetMatrix)
aa <- as.matrix(NetMatrix)
View(aa)
networkPlot(NetMatrix, n=30, normalize = "association",labelsize=1)
networkPlot(NetMatrix, n=30, normalize = "association",labelsize=1)
library(igraph)
library(bibliometrix)
data(scientometrics)
NetMatrix <- biblioNetwork(scientometrics, analysis = "co-occurrences",
network = "authors", sep = ";")
networkPlot(NetMatrix, n=30, normalize = "association",labelsize=1)
networkPlot(NetMatrix, n=30, normalize = "association",labelsize=1)
par(mar=c(1,1,1,1))
networkPlot(NetMatrix, n=30, normalize = "association",labelsize=1)
library(igraph)
library(bibliometrix)
data(scientometrics)
NetMatrix <- biblioNetwork(scientometrics, analysis = "co-occurrences",
network = "authors", sep = ";")
par(mar=c(1,1,1,1))
networkPlot(NetMatrix, n=30, normalize = "association",labelsize=1)
net <- networkPlot(NetMatrix, n=30, normalize = "association",labelsize=1)
aa <- as.matrix(NetMatrix)
net2 <- networkPlot(aa, n=30, normalize = "association", labelsize=1)
par(mar=c(1,1,1,1))
net <- networkPlot(NetMatrix, n=30, normalize = "association", labelsize=1, cluster = "kamada")
aa <- as.matrix(NetMatrix)
par(mar=c(1,1,1,1))
net2 <- networkPlot(aa, n=30, normalize = "association", labelsize=1, cluster = "kamada")
View(aa)
library(igraph)
library(bibliometrix)
data(scientometrics)
NetMatrix <- biblioNetwork(scientometrics, analysis = "co-occurrences",
network = "authors", sep = ";")
par(mar=c(1,1,1,1))
net <- networkPlot(NetMatrix, n=230, normalize = "association", labelsize=1, cluster = "kamada")
aa <- as.matrix(NetMatrix)
par(mar=c(1,1,1,1))
net2 <- networkPlot(aa, n=230, normalize = "association", labelsize=1, cluster = "kamada")
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_BBL_Graph.r')
class(NetMatrix)
View(aa)
View(NetMatrix)
library(readxl)
library(quanteda)
library(igraph)
library(bibliometrix)
library(CINNA)
comment_nlp <- read_excel("./source/comment_cooc_freq.xlsx")
rn1 <- as.matrix(comment_nlp[,1])
comment_nlp <- comment_nlp[2:497]
#comment_nlp <- comment_nlp[2:13]
row.names(comment_nlp) <- rn1
adjmt <- as.matrix.data.frame(comment_nlp)
#total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="max")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, normalize=NULL, n=vcount(G1), type="kamada")
net2VOSviewer(net, vos.path = "VOS")
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')
net2VOSviewer(net, vos.path = "VOS")
library(readxl)
library(quanteda)
library(igraph)
library(bibliometrix)
library(CINNA)
comment_nlp <- read_excel("./source/comment_cooc_freq.xlsx")
rn1 <- as.matrix(comment_nlp[,1])
comment_nlp <- comment_nlp[2:497]
#comment_nlp <- comment_nlp[2:13]
row.names(comment_nlp) <- rn1
adjmt <- as.matrix.data.frame(comment_nlp)
#total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="max")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, normalize=NULL, n=vcount(G1), type="kamada")
View(net)
class(net)
net[["cluster_obj"]]
install.packages("writexl")
library(writexl)
ddf <- data.frame(net[["cluster_obj"]])
class(net[["cluster_obj"]])
et[["cluster_obj"]]
net[["cluster_obj"]]
View(net)
net[["cluster_obj"]["membership"]]
net["cluster_obj"]["membership"]
net["cluster_obj"]
membership(net["cluster_obj"])
clusObj <- net[["cluster_obj"]]
View(clusObj)
clusObj[["membership"]]
clusObj[["memberships"]]
clear
class(clusObj)
clusObj
print(clusObj)
ata.frame(clusObj)
data.frame(clusObj)
as.numeric(clusObj)
as.numeric(unlist(clusObj))
unlist(clusObj)
net <- networkPlot(adjmt, normalize=NULL, n=vcount(G1), cluster="louvain", type="kamada")
clusObj <- net[["cluster_obj"]]
unlist(clusObj)
data.frame(unlist(clusObj))
ddf <- data.frame(unlist(clusObj))
write_xlsx(ddf,"./output/community.xlsx")
clusObj['membership']
clusObj['memberships']
clusObj[["membership"]]
clusObj[["memberships"]]
clusObj[["algorithm"]]
print(clusObj[["algorithm"]])
par(mar=c(1,1,1,1))
networkPlot(adjmt, normalize=NULL, n=vcount(G1), cluster="louvain", type="kamada")
library(readxl)
library(quanteda)
library(igraph)
library(bibliometrix)
library(CINNA)
library(writexl)
comment_nlp <- read_excel("./source/comment_cooc_freq.xlsx")
rn1 <- as.matrix(comment_nlp[,1])
comment_nlp <- comment_nlp[2:497]
#comment_nlp <- comment_nlp[2:13]
row.names(comment_nlp) <- rn1
adjmt <- as.matrix.data.frame(comment_nlp)
#total_occurrences <- colSums(adjmt)
G1 <- graph_from_adjacency_matrix(adjmt, weighted=TRUE, mode="max")
par(mar=c(1,1,1,1))
net <- networkPlot(adjmt, normalize=NULL, n=vcount(G1), cluster="louvain", type="kamada")
net2VOSviewer(net, vos.path = "VOS")
net2VOSviewer(net, vos.path = "VOS")
source('E:/master_BADS/IS_BADS/QAP_Test_PPSNA_R/PPSNA_VOS_Graph.r')