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Identify Key Routes in Citation Networks

Source: R/sniff_key_route.R
sniff_key_route.Rd

This function identifies and visualizes key citation routes within scientific networks by analyzing the most significant citation paths between publications. The algorithm implements the key-route search from the integrated main path analysis approach described in Liu & Lu (2012).

Usage

sniff_key_route(network, scope = "network", citations_percentage = 1)

Arguments

network

A network object of class tbl_graph or igraph containing citation data, or a list object generated by sniff_groups() when scope = "groups"

scope

Character string specifying the analysis scope. Must be either "network" (for full network analysis) or "groups" (for group-wise analysis of a grouped network)

citations_percentage

Numeric value between 0 and 1 indicating the percentage of top SPC edges eligible for the key-route path. Default is 1 (all edges)

Value

A list containing for each group:

  • plot - A ggplot2 object visualizing the key citation route

  • data - A tibble with publication details (name, TI, AU, PY) of nodes in the key route

Details

The function implements the key-route search from Liu & Lu (2012):

  1. Computes Search Path Count (SPC) for each citation link using an efficient O(V+E) algorithm based on topological sort. SPC measures how many source-to-sink paths traverse each link.

  2. Selects the key-route: the link with the highest SPC value.

  3. Searches forward from the end node of the key-route, greedily following the outgoing link with the highest SPC, until a sink is reached.

  4. Searches backward from the start node of the key-route, greedily following the incoming link with the highest SPC, until a source is reached.

The SPC is computed as forward[u] * backward[v] for each edge (u, v), where forward[u] counts paths from any source to u and backward[v] counts paths from v to any sink (Batagelj, 2003). This guarantees the most significant link is always included in the key-route path.

References

Liu JS, Lu LYY. An integrated approach for main path analysis: Development of the Hirsch index as an example. Journal of the American Society for Information Science and Technology. 2012;63(3):528-542. doi:10.1002/asi.21692

Batagelj V. Efficient algorithms for citation network analysis. University of Ljubljana, Institute of Mathematics, Physics and Mechanics, Department of Theoretical Computer Science, Preprint Series. 2003;41:897.

Examples

if (FALSE) { # \dontrun{
# Example with network scope
result <- sniff_key_route(my_network, scope = "network", citations_percentage = 0.8)

# Example with groups scope
grouped_network <- sniff_groups(data)
result <- sniff_key_route(grouped_network, scope = "groups")

# Access results for a specific group
result$group_name$plot
result$group_name$data
} # }