Visualize 2D Technological Trajectories from Group Evolution

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 and groups_attributes, typically produced by plot_groups_trajectories(). The groups_similarity element must be a named list of edge tables (one per group) with at least from, to, and weight; the groups_attributes element must be a named list of node tables containing, among others, network_until, quantity_papers, prop_tracked_intra_group, tracked_documents, and PY.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).

Value

A ggplot2 object visualizing the technological trajectories.

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
)
} # }