我有具有 1000 个顶点的二分列表（帖子、单词类别），并且想使用快速和贪婪的算法进行社区检测，但我不确定是否必须在二分图或二分投影上运行它。
我的二分列表如下所示：
post word
1 66 2
2 312 1
3 432 7
4 433 7
5 434 1
6 435 5
7 436 1
8 437 4
当我在没有投影的情况下运行它时，我在第二步中遇到了聚类问题：
### Load bipartie list and create graph ###
bipartite_list <- read.csv("bipartite_list_tnf.csv", header = TRUE, sep = ";")
bipartite_graph <- graph.incidence(bipartite_list)
g<-bipartite_graph
fc <- fastgreedy.community(g) ## communities / clusters
set.seed(123)
l <- layout.fruchterman.reingold(g, niter=1000, coolexp=0.5) ## layout
membership(fc)
# 2. checking who is in each cluster
cl <- data.frame(name = fc$post, cluster = fc$membership, stringsAsFactors=F)
cl <- cl[order(cl$cluster),]
cl[cl$cluster==1,]
# 3. preparing data for plot
d <- data.frame(l); names(d) <- c("x", "y")
d$cluster <- factor(fc$membership)
# 4. plot with only nodes, colored by cluster
p <- ggplot(d, aes(x=x, y=y, color=cluster))
pq <- p + geom_point()
pq
也许我必须在投影上运行社区检测？但是后来我总是失败，因为投影不是图形对象：
bipartite_graph <- graph.incidence(bipartite_list)
#projection (both directions)
projection_word_post <- bipartite.projection(bipartite_graph)
fc <- fastgreedy.community(projection_word_post)
Fehler in fastgreedy.community(projection_word_post) : Not a graph object
我很乐意提供帮助！