Sept 11

1. Here is the data read into links and nodes, and the network.

Sept11_Network <- graph_from_data_frame(Sept11_links, 
                                           vertices = Sept11_nodes, 
                                           directed = F)

2. This is the density of the network.

Sept11_Network %>% 
  vcount()

[1] 62

Sept11_Network %>%
  ecount()

[1] 151

Sept11_Network %>% 
  edge_density()

[1] 0.07985193

The density of this network is .08.

3. Make a histogram of the distances in the network.

Sept11_Network %>% 
  distances() %>% 
  as.vector() %>%              
  as_tibble() %>%              
  plot_ly(x = ~value) %>% 
  add_histogram()

Most relationships in this network were 3 connections apart.

4. Find the length of the diameter of the network.

Sept11_Network %>% 
  get_diameter() %>% 
  length()

[1] 6

The diameter of the network is 6.

5. Here is label, title, degree and value = degree mutated into the data.

Sept11_nodes <- Sept11_nodes %>% 
  mutate(label = name)

Sept11_nodes <- Sept11_nodes %>% 
  mutate(title = name)

Sept11_nodes <- Sept11_nodes %>% 
  mutate(degree = degree(Sept11_Network))

Sept11_nodes <- Sept11_nodes %>% 
  mutate(value = degree) 

These changes have had an impact in the columns and will have an impact on the upcoming graph(s).

6. Mutate betweenness into the links data, and set it to value.

Sept11_links <- Sept11_links %>% 
  mutate(betweenness = edge_betweenness(Sept11_Network)) %>%
  mutate(value = betweenness)
 

We will see the results of these added columns on our graph(s)

7. This is a diagram of the network.

  visNetwork(Sept11_nodes, 
           Sept11_links, 
           main = "Network of Terrorists involved in the 9/11 Attack") %>% 
  visIgraphLayout(layout = "layout_nicely") %>% 
  visOptions(highlightNearest = T, nodesIdSelection = T)

This Network is not very tightly packed there are almost three spread apart groups.

8. Here are the communities in the network and another diagram displaying the colored groups.

Sept11_nodes <- Sept11_nodes %>% 
  mutate(group = membership(infomap.community(Sept11_Network)))

Sept11_nodes %>% 
  datatable()

NA

visNetwork(Sept11_nodes, 
           Sept11_links, 
           main = "Network of Terrorists involved in the 9/11 Attack") %>% 
  visIgraphLayout(layout = "layout_nicely") %>% 
  visOptions(highlightNearest = T, nodesIdSelection = T)

NA

With the colors its much more obvious that there are 6 groups.