在R中，在R中使用tdm或dtm上的IGRAPHE绘制关键字/单词关联（findAssocs）？

我想基于R中的某些内容创建一个，但我不知道如何超越绘制整个术语文档矩阵：

# Network analysis
library(igraph)
# load tdm data

# create matrix
Neg.m <- as.matrix(Ntdm_nonsparse)

# to boolean matrix
Neg.m[Neg.m>=1] <- 1

# to term adjacency matrix
# %*% is product of 2 matrices
Neg.m2 <- Neg.m %*% t(Neg.m)
Neg.m2[5:10,5:10]

# build graph with igraph ####
library(igraph)
# build adjacency graph
Neg.g <- graph.adjacency(Neg.m2, weighted=TRUE, mode="undirected")
# remove loops
Neg.g <- simplify(Neg.g)
# set labels and degrees of vertices
V(Neg.g)$label <- V(Neg.g)$name
V(Neg.g)$degree <- degree(Neg.g)

# plot layout fruchterman.reingold
layout1 <- layout.fruchterman.reingold(Neg.g)
plot(Neg.g, layout=layout1, vertex.size=20, 
     vertex.label.color="darkred")

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换句话说，我想可视化一个特定关键字与R中其他关键字之间的联系，但我不知道如何实现

遵循word\u网络图（qdap包）中的示例

findAssocs(Ntdm, "verizon", .06)
$verizon
           att       switched         switch       wireless         basket         09mbps         16mbps 
          0.16           0.13           0.11           0.11           0.10           0.09           0.09 
        32mbps           4gbs           5gbs        cheaper            ima         landry          nudge 
          0.09           0.09           0.09           0.09           0.09           0.09           0.09 
         sears           wink      collapsed      expensive         sprint          -fine           -law 
          0.09           0.09           0.08           0.08           0.08           0.07           0.07 
         11yrs            380            980         alltel        callled         candle           cdma 
          0.07           0.07           0.07           0.07           0.07           0.07           0.07 
       concert    consequence    de-evolving          dimas          doria          fluke           left 
          0.07           0.07           0.07           0.07           0.07           0.07           0.07 
        london           lulz        lyingly           niet        outfits     pocketbook           puny 
          0.07           0.07           0.07           0.07           0.07           0.07           0.07 
     recentely         redraw    reinvesting      reservoir    satellite's         shrimp   stratosphere 
          0.07           0.07           0.07           0.07           0.07           0.07           0.07 
     strighten       switchig      switching        undergo     wheelchair wireless-never          worth 
          0.07           0.07           0.07           0.07           0.07           0.07           0.07 
          yeap           1994            299       cheapest           com'          comin        crushes 
          0.07           0.06           0.06           0.06           0.06           0.06           0.06 
  hhahahahahah          mache          metro      metro-nyc        must've         rising       sabotage 
          0.06           0.06           0.06           0.06           0.06           0.06           0.06 
wholeheartedly 
          0.06