Build a Citation Network from an iCite Corpus — citation

Converts an icites data.table into a tidy graph representation (nodes + edges) suitable for igraph or tidygraph. Only edges where both endpoints are present in the corpus are retained, so the graph is bounded to the papers you already have metadata for.

citation_network(icites)

Arguments

icites: A data.table returned by get_records(endpoint = "icites"). Must contain pmid and citation_net columns.

Value

A named list with two data.tables:

nodes: One row per PMID. Contains all iCite metadata columns except citation_net. Key columns: pmid, relative_citation_ratio, nih_percentile, is_clinical.
edges: One row per within-corpus directed citation. Columns: from_pmid (the citing paper), to_pmid (the cited paper).

Details

RCR and is_clinical are carried as node attributes, making the resulting graph immediately weighted by field-normalized impact and enabling bench-to-bedside edge filtering without any additional API calls.

Examples

if (FALSE) { # \dontrun{
# network from a seed corpus
pmids |>
  get_records(endpoint = "icites") |>
  citation_network()

# expand first, then fetch iCite metadata for the full network
snowball <- pmids |>
  get_records(endpoint = "icites") |>
  citation_snowball()

snowball$pmid |>
  get_records(endpoint = "icites") |>
  citation_network()

# translational footprint: filter to bench -> clinical edges
snowball <- pmids |>
  get_records(endpoint = "icites") |>
  citation_snowball()

net <- snowball$pmid |>
  get_records(endpoint = "icites") |>
  citation_network()

clinical_edges <- net$edges |>
  merge(net$nodes[, .(pmid, is_clinical)],
        by.x = "to_pmid", by.y = "pmid") |>
  subset(is_clinical == TRUE)
} # }