Importing Required Packages

packages = c('igraph', 'tidygraph', 'ggraph', 'visNetwork', 'lubridate', 'tidyverse')

for(p in packages){library
  if(!require(p, character.only = T)){
    install.packages(p)
  }
  library(p, character.only = T)
}

Importation of Data

GAStech_nodes <- read_csv("data/GAStech_email_node.csv")
GAStech_edges <- read_csv("data/GAStech_email_edge-v2.csv")

Data Wrangling

GAStech_edges$SentDate  = dmy(GAStech_edges$SentDate)
GAStech_edges$Weekday = wday(GAStech_edges$SentDate, label = TRUE, abbr = FALSE)
GAStech_edges_aggregated <- GAStech_edges %>%
  filter(MainSubject == "Work related") %>%
  group_by(source, target, Weekday) %>%
    summarise(Weight = n()) %>%
  filter(source!=target) %>%
  filter(Weight > 1) %>%
  ungroup()
GAStech_edges_aggregated
## # A tibble: 1,456 x 4
##    source target Weekday   Weight
##     <dbl>  <dbl> <ord>      <int>
##  1      1      2 Monday         4
##  2      1      2 Tuesday        3
##  3      1      2 Wednesday      5
##  4      1      2 Friday         8
##  5      1      3 Monday         4
##  6      1      3 Tuesday        3
##  7      1      3 Wednesday      5
##  8      1      3 Friday         8
##  9      1      4 Monday         4
## 10      1      4 Tuesday        3
## # ... with 1,446 more rows

Creating the Network Object

GAStech_graph <- tbl_graph(nodes = GAStech_nodes, edges = GAStech_edges_aggregated, directed = TRUE)
GAStech_graph %>%
  activate(edges) %>%
  arrange(desc(Weight))
## # A tbl_graph: 54 nodes and 1456 edges
## #
## # A directed multigraph with 1 component
## #
## # Edge Data: 1,456 x 4 (active)
##    from    to Weekday Weight
##   <int> <int> <ord>    <int>
## 1    40    41 Tuesday     23
## 2    40    43 Tuesday     19
## 3    41    43 Tuesday     15
## 4    41    40 Tuesday     14
## 5    42    41 Tuesday     13
## 6    42    40 Tuesday     12
## # ... with 1,450 more rows
## #
## # Node Data: 54 x 4
##      id label           Department     Title           
##   <dbl> <chr>           <chr>          <chr>           
## 1     1 Mat.Bramar      Administration Assistant to CEO
## 2     2 Anda.Ribera     Administration Assistant to CFO
## 3     3 Rachel.Pantanal Administration Assistant to CIO
## # ... with 51 more rows

Task 1: Static Organisation Graph

With reference to Section 6.1 of Hands-on Exercise 10, the original static plot is as follows:
g <- GAStech_graph %>%
  mutate(betweenness_centrality = centrality_betweenness()) %>%
  mutate(closeness_centrality = centrality_closeness()) %>%
  ggraph(layout = "nicely") + 
  geom_edge_link(aes()) +
  geom_node_point(aes(colour = closeness_centrality, size=betweenness_centrality))

g + theme_graph()

Improve the code chunk used by using the latest functions provided in ggraph2.0
g <- ggraph(GAStech_graph, layout = "nicely") + 
  geom_edge_link(aes()) +
  geom_node_point(aes(colour = centrality_closeness(), size=centrality_betweenness()))

g + theme_graph()

ggraph2.0 allows for access to tidygraph algorithms in ggraph code, hence we can compute the centrality measures directly.

Identify three aspects of the graph visualisation in Section 6.1 that can be improved.
No. Issue Proposed Improvement
1 The edge colours are too dark, which may visually interfere with the nodes. This makes it difficult to differentiate the edges easily according to importance. Change the edge colour to a lighter one which is more visually similar to the background colour, such as light grey. The edge weights can also be represented by the opacity of the edge line.
2 The node colour used is not indicative of the departments which the node belongs to, which would be an important feature in an organisation chart. The nodes which overlap also cannot be differentiated due to the node colours. Colour the nodes according to department, and use opacity to represent the closeness centrality instead.
3 The nodes are not labelled, making it difficult to know which node represents which employee. Label the nodes by employee name.
Provide the sketch of your alternative design:

Using appropriate ggraph functions, plot the alternative design. 
g_alt <- ggraph(GAStech_graph, layout='kk') + 
  geom_edge_link(colour = "grey50", aes(edge_alpha=Weight)) +
  geom_node_point(aes(colour = Department, size=centrality_betweenness(), alpha=centrality_closeness())) +
  geom_text(aes(x= g_alt[["data"]][["x"]], y=g_alt[["data"]][["y"]],label=g_alt[["data"]][["label"]]),size=2, alpha=0.8)
            
g_alt + theme_graph()

Task 2: Interactive Organisation Graph

Data Preparation
GAStech_edges_aggregated <- GAStech_edges %>%
  left_join(GAStech_nodes, by = c("sourceLabel" = "label")) %>%
  rename(from = id) %>%
  left_join(GAStech_nodes, by = c("targetLabel" = "label")) %>%
  rename(to = id) %>%
  filter(MainSubject == "Work related") %>%
  group_by(from, to) %>%
    summarise(weight = n()) %>%
  filter(from!=to) %>%
  filter(weight > 1) %>%
  ungroup()

GAStech_nodes <- GAStech_nodes %>%
  rename(group = Department)
Original Design
visNetwork(GAStech_nodes, GAStech_edges_aggregated) %>%
  visIgraphLayout(layout = "layout_with_fr") %>%
  visOptions(highlightNearest = TRUE, nodesIdSelection = TRUE)
Improved Design

Improvement 1: When a name is selected from the drop-down list, the corresponding node will not only be highlighted but also will be labelled. Furthermore, all the linked nodes of the selected node will also be labelled too.

Improvement 2: When a node of the interactive graph is selected, the node will not only be highlighted but also will be labelled. Furthermore, all the linked nodes of the selected node will be labelled as well. 

visNetwork(GAStech_nodes, GAStech_edges_aggregated) %>%
  visIgraphLayout(layout = "layout_with_fr") %>%
  visNodes(label=GAStech_nodes$id, shape="circle") %>%
  visOptions(highlightNearest = list(enabled = TRUE, labelOnly = FALSE), nodesIdSelection = TRUE)
Identify three aspects of the graph visualisation in Section 7.4 that can be improved.
No. Issue Proposed Improvement
1 The node labels cannot be seen unless the viewer zooms in, which might not be practical nor intuitive. The labels also do not provide much information about the node. Include node information on hover, such that it provides further detail to the user. Including information in the tooltip also allows the labels to only be showed upon user interaction, ensuring that the graph will not be too messy.
2 There is no legend provided to show an indication of what each colour represents. Include a legend to show the corresponding department for each colour.
3 There is a lack of directionality and weight reflected in the graph. In this context, weight would be the number of emails sent from one employee to another. Directionality would reflect the sender and receiver. All these are important information which should be included in the network. Include indication of directionality on the edges, as well as the weights.
Provide the sketch of your alternative design.

Using appropriate visNetwork functions, plot the alternative design.

Data Preparation 

GAStech_edges_aggregated <- GAStech_edges_aggregated %>%
  rename(value = weight)

GAStech_nodes$title = paste0(GAStech_nodes$label, "<br> Title: ", GAStech_nodes$Title)

Improved Network Graph

visNetwork(GAStech_nodes, GAStech_edges_aggregated) %>%
  visIgraphLayout(layout = "layout_with_fr") %>%
  visNodes(label=id, shape="circle") %>%
  visEdges(arrows = "to", color = list(highlight = "blue")) %>%
  visLegend(main = "Department") %>%
  visOptions(highlightNearest = list(enabled = TRUE, labelOnly = FALSE, degree=1), nodesIdSelection = TRUE)

Sources:
https://www.rdocumentation.org/packages/visNetwork/versions/2.0.8/topics/visOptions
https://www.data-imaginist.com/2017/ggraph-introduction-edges/
https://www.data-imaginist.com/2017/ggraph-introduction-nodes/
https://stackoverflow.com/questions/46664645/r-visnetwork-igraph-weighted-network-visualization-with-visedges