How to show where networkpersons live and how they are connected - ggplot2

Question

I want to show where network people live and how they are connected. First, I drew a map of the 15 municipalities (based on SpatialPolygonsDataFrame, geom_polygon of ggplot2). Second, I placed the network people around the centroids of the polygons. After the third variant in "Three ways of visualizing a graph on a map" by Markus Konrad, I have so far created two layers https://datascience.blog.wzb.eu/2018/05/ 31 / three-ways-of-visualizing-a-graph-on-a-map /). As mapcoords I used coord_fixed (ratio = 1/1). To achieve a good result, I had to make manual adjustments in annotation_custom.
My questions:
First, is there a way to adapt the layers to each other without manual intervention?
Second, are there simpler solutions to geographically locate network people and their connections?my result so far
maptheme <- theme(panel.grid = element_blank()) +
theme(axis.text = element_blank()) +
theme(axis.ticks = element_blank()) +
theme(axis.title = element_blank()) +
theme(legend.position = "bottom") +
theme(panel.grid = element_blank()) +
theme(panel.background = element_rect(fill = "#596673")) +
theme(plot.margin = unit(c(0, 0, 0.5, 0), 'cm'))
mapcoords <- coord_fixed(ratio=1/1)
theme_transp_overlay <- theme(
panel.background = element_rect(fill = "transparent", color = NA),
plot.background = element_rect(fill = "transparent", color = NA))
ArlMap <- ggplot(ARLmap.data, aes(long, lat)) +
geom_polygon(aes(group=group), colour='white', fill='grey')+
theme(axis.text=element_blank())+
theme(axis.ticks=element_blank())+
theme(axis.title=element_blank())+
mapcoords + maptheme
nodes <- ggplot(nwdata) +
geom_point(aes(x = xkor, y = ykor, size = Btw),
shape = 21, fill = "white", color = "black", # draw nodes
stroke = 0.5) +
scale_size_continuous(guide = FALSE, range = c(1, 6)) +
mapcoords + maptheme + theme_transp_overlay
ArlMap +
annotation_custom(ggplotGrob(nodes), xmin = min(ARLmap.data$long)+900, xmax = max(ARLmap.data$long)-1200, ymin = min(ARLmap.data$lat)+1500, ymax = max(ARLmap.data$lat))
...

Answer 1

I'm at the goal. I came to the solution by consistently starting from a geographical approach: 1. The nodes of the network receive lon / lat coordinates. These are determined as rotation coordinates around the centroids of the geographical unit. 2. The connections between the nodes are provided with new start and end points on the basis of the lon / lat coordinates. 3. The plot is limited to the basic functions plot, lines and points.enter image description here