dynamic.RmdWhat is a dynamic graph? A graph that includes an additional dimension which renders is dynamic. Here we’ll create a temporal graph
Start by making the graph, see “Get Started” vignette if you do not know how to get tweets.
tweets %>%
gt_edges(screen_name, mentions_screen_name, created_at) %>%
gt_nodes() %>%
gt_dyn() %>%
gt_collect() -> netA few things to note.
created_at in gt_edges as we want to know the time at which the edge is created.gt_nodes
gt_dyn (short for “dynamic”) to get the dynamic graph.Let’s look at the output.
| source | target | created_at | n | end |
|---|---|---|---|---|
| _colinfay | kevin_ushey | 2019-03-11 14:03:04 | 1 | 2019-03-12 22:44:19 |
| _j_sinclair | holomarked | 2019-03-11 20:46:11 | 1 | 2019-03-12 22:44:19 |
| _j_sinclair | jennybryan | 2019-03-11 20:46:11 | 1 | 2019-03-12 22:44:19 |
| _j_sinclair | nic_crane | 2019-03-11 20:46:11 | 1 | 2019-03-12 22:44:19 |
| _j_sinclair | rbloggers | 2019-03-11 20:46:11 | 1 | 2019-03-12 22:44:19 |
| _j_sinclair | rdpeng | 2019-03-11 20:46:11 | 1 | 2019-03-12 22:44:19 |
The edges include the created_at column (date time when the tweet is posted).
| nodes | start | end | type | n |
|---|---|---|---|---|
| _colinfay | 2019-03-11 14:03:04 | 2019-03-12 22:44:19 | user | 4 |
| _j_sinclair | 2019-03-11 20:46:11 | 2019-03-12 22:44:19 | user | 5 |
| _psyguy | 2019-03-12 13:47:30 | 2019-03-12 22:44:19 | user | 1 |
| _willdebras | 2019-03-12 17:37:03 | 2019-03-12 22:44:19 | user | 1 |
| 10xgenomics | 2019-03-10 20:04:54 | 2019-03-12 22:44:19 | user | 1 |
| a_bunn | 2019-03-12 16:29:47 | 2019-03-12 22:44:19 | user | 1 |
The nodes include start and end column, this is added by the gt_dyn function; which, in effect, simply computes when the node should appear on the graph.
I use sigmajs to visualise the dynamic graph, please see the website if you want to understand the code below, being a different package I do not get into this here. In brief, I convert date time to numeric and rescale edge appearances between 0 and 10 seconds (so that the animation lasts 10 seconds), I then add 5 seconds so that the animation starts after 5 seconds (to give you a chance to see it in action).
Click the trigger to add the edges.
library(sigmajs)
# convert to numeric & rescale
edges <- net$edges %>%
dplyr::mutate(
id = 1:dplyr::n(),
created_at = as.numeric(created_at),
created_at = (created_at - min(created_at)) / (max(created_at) - min(created_at)),
created_at = created_at * 10000
)
nodes <- net$nodes %>%
dplyr::mutate(
id = nodes,
label = nodes,
size = n
)
# graph layout
nodes <- sg_get_layout(nodes, edges)
nodes <- sg_get_cluster(nodes, edges, colors = c("#2780e3", "#d3d3d3")) # cluster
sigmajs() %>%
sg_nodes(nodes, id, size, label, x, y, color) %>%
sg_add_edges(edges, created_at, id, source, target,
cumsum = FALSE, refresh = TRUE) %>%
sg_button("add_edges", tags$i(class = "fa fa-play"), class = "btn btn-primary") %>%
sg_settings(defaultNodeColor = "#1967be")Note that you can also dynamically add nodes, much of it explained in the twinetbook.
Twinetbook