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Visualize 2D Technological Trajectories from Group Evolution

Source: R/plot_groups_lineage_2d.R
plot_groups_lineage_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_groups_lineage_2d(
  groups_lineage,
  group = "c1g1",
  jaccard_similarity = 0.01,
  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,
  color_by = c("py_deviation", "final_group_share")
)

Arguments

groups_lineage

A list with components groups_similarity and groups_attributes, typically produced by sniff_groups_lineage(). 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: "c1g1").

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

Kept for backward compatibility; no longer applied, as labels are auto-positioned (repelled) with a white halo so they stay readable over dark nodes and do not overlap.

label_horizontal_position

Kept for backward compatibility; not applied (see label_vertical_position).

label_angle

Kept for backward compatibility; not applied (labels are auto-positioned).

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).

color_by

What the node color encodes: "py_deviation" (default) colors by the average publication-year deviation (PY.sd); "final_group_share" colors each node by the share of its papers that belong to group's last-year cluster (a plasma palette, 0-100\ showing how much of each earlier cluster funnels into the final group. The latter requires docs_per_group in groups_lineage.

Value

A ggplot2 object visualizing the technological trajectories.

Details

A descriptive stock view of one group's lineage network. A group's lineage can share year communities with other groups (soft membership), so this view makes no trajectory claims – for detection see sniff_trajectory_braid().

See also

Other visualization: plot_groups_influence_matrix(), plot_groups_influence_network(), plot_groups_lineage_3d(), plot_groups_map(), plot_groups_map_animation(), plot_groups_map_interactive(), plot_groups_per_year(), plot_trajectory_confluence(), plot_trajectory_confluence_interactive(), plot_trajectory_confluence_matrix(), plot_trajectory_dag(), plot_trajectory_dag_interactive(), plot_trajectory_dispersion(), plot_trajectory_dynamics(), plot_trajectory_dynamics_interactive(), plot_trajectory_formation(), plot_trajectory_lines_2d(), plot_trajectory_lines_3d()

Examples

if (FALSE) { # \dontrun{
# Compute trajectories first
traj_data <- sniff_groups_lineage(groups_cumulative)

# Visualize a specific group (pass the whole object; the function extracts what it needs internally)
plot_groups_lineage_2d(
  groups_lineage = traj_data,
  group = "c1g5",
  jaccard_similarity = 0.3
)
} # }