
Visualize 2D Technological Trajectories from Group Evolution
Source:R/plot_group_trajectory_2d.R
plot_group_trajectories_2d.Rd
Creates a 2D visualization of technological trajectories based on group similarity metrics, showing the evolution of research groups over time with node size representing group importance and color representing publication-year deviation.
Usage
plot_group_trajectories_2d(
groups_cumulative_trajectories,
group = "component1_g01",
jaccard_similarity = 0.1,
prop_tracked_intra_group_treshold = 0.2,
label_type = "size",
label_vertical_position = 0,
label_horizontal_position = 0,
label_angle = 0,
time_span = NA,
show_legend = TRUE
)
Arguments
- groups_cumulative_trajectories
A list with components
groups_similarity
andgroups_attributes
, typically produced byplot_groups_trajectories()
. Thegroups_similarity
element must be a named list of edge tables (one per group) with at leastfrom
,to
, andweight
; thegroups_attributes
element must be a named list of node tables containing, among others,network_until
,quantity_papers
,prop_tracked_intra_group
,tracked_documents
, andPY.sd
.- group
The specific group to visualize (default: "component1_g01").
- jaccard_similarity
Minimum Jaccard similarity threshold for connections (default: 0.1).
- prop_tracked_intra_group_treshold
Minimum proportion of tracked intra-group documents for nodes to be included (default: 0.2).
- label_type
Type of labels to display on nodes ("size" for weighted size or "id" for group IDs).
- label_vertical_position
Vertical adjustment for node labels (default: 0).
- label_horizontal_position
Horizontal adjustment for node labels (default: 0).
- label_angle
Angle for node labels (default: 0).
- time_span
Optional vector of years to display; if
NA
, shows all (default:NA
).- show_legend
Logical indicating whether to show the color legend (default:
TRUE
).
Examples
if (FALSE) { # \dontrun{
# Compute trajectories first
traj_data <- plot_groups_trajectories(groups_cumulative)
# Visualize a specific group (pass the whole object; the function extracts what it needs internally)
plot_group_trajectories_2d(
groups_cumulative_trajectories = traj_data,
group = "component1_g05",
jaccard_similarity = 0.3
)
} # }