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correspsearch_letters — Historical correspondence networks (LetterSampo: correspSearch and Finland)

Description

Networks of historical letters from the knowledge graphs of the LetterSampo project (Semantic Computing Research Group, Aalto University and University of Helsinki), which harmonized the metadata of letters (sender, recipient, date and places) from several sources:

  • correspsearch_v2 and correspsearch_v1: the letters of correspSearch, the service of the Berlin-Brandenburg Academy of Sciences that aggregates the metadata of letters (in the CMIF format) from hundreds of printed and digital scholarly editions of correspondence, mostly of German-speaking persons from the 16th to the 20th century, as converted to RDF by LetterSampo, in the two versions of the data publication (v2 of June 2022, with 132,138 letters, and v1 of February 2022). correspSearch has grown since; only these conversions are available as a bulk download.
  • finland: LetterSampo Finland (version 1.0.0, May 2025), the letters of 19th-century (and later) Finnish archives and editions (the Finnish Literature Society, the National Archives and National Library of Finland, the Swedish Literature Society in Finland, Åbo Akademi University Library, the editions of the letters of Topelius, Snellman, Lönnrot, Edelfelt, ...), with about 1.3 million letters.

Each node is a correspondent (a person or a group, e.g. a society, a firm or an office), as identified by the sources and harmonized by LetterSampo, and a directed edge from $i$ to $j$ is a letter sent by $i$ to $j$; letters with several senders or recipients give an edge for each pair. Pairs of correspondents exchanged many letters (multigraphs). Letters without a known sender or recipient are left out. In finland, the correspondents of the sources ("proxies") are merged into the harmonized actors of LetterSampo, as in its portal; proxies without a harmonized actor are kept as they are.

The networks have the following properties:

  • (Node) name: the name of the correspondent.
  • (Node) uri: the URI of the correspondent in the knowledge graph.
  • (Node) type: Person or Group (correspsearch_*: both, for a few actors typed as both).
  • (Node) gender: Female, Male, or empty if not known.
  • (Node) birth, death: the dates of birth and death (or of the beginning and end of groups), as in the data (YYYY-MM-DD, or a year), or empty.
  • (Node) gnd, viaf, wikidata (correspsearch_*): the identifiers of the correspondent in the GND (German National Library), VIAF and Wikidata, or empty.
  • (Node) sent_letters, received_letters (finland): the numbers of letters sent and received by the actor in LetterSampo Finland.
  • (Edge) date_from, date_to: the range of possible dates of the letter (YYYY-MM-DD, or as given in finland, e.g. 1899-1909), or empty if unknown.
  • (Edge) label: the label of the letter in the knowledge graph (e.g. "1520 Jul 22: Melanchthon, Philipp (Wittenberg) to Spalatin, Georg (Lochau)").
  • (Edge) place_from, place_to (correspsearch_*): the places from which the letter was sent and to which it was sent, or empty.
  • (Edge) latitude_from, longitude_from, latitude_to, longitude_to (correspsearch_*): the coordinates of these places (NaN if not known).
  • (Edge) source: the edition (correspsearch_*) or the source organization (finland) of the letter's metadata.
  • (Edge) fonds (finland): the archival fonds (collection) of the letter.
Tags
Social Communication Offline Unweighted Multigraph Timestamps Metadata
Added
2026-10-31
Citation
Upstream URL OK
https://doi.org/10.5281/zenodo.6631357
https://doi.org/10.5281/zenodo.15210590
https://zenodo.org/records/6631357
https://zenodo.org/records/15210590
https://correspsearch.net/
https://seco.cs.aalto.fi/projects/rrl/
https://kirjesampo.fi/
Upstream license
CC BY 4.0, https://creativecommons.org/licenses/by/4.0/
Networks
Tip: click on a column header to sort the list, or hover over it for a description.
Column legend
$\left<k\right>$
Mean degree
$\sigma_k$
Standard deviation of the degrees
$\lambda_h$
Largest eigenvalue of the Hashimoto (non-backtracking) matrix
$\tau$
Random walk mixing time
$r$
Degree assortativity
$c$
Global clustering coefficient
$\oslash$
(Pseudo-) diameter
$S$
Relative size of the largest component
NPs
Node properties
EPs
Edge properties
Name Nodes Edges $\left<k\right>$ $\sigma_k$ $\lambda_h$ $\tau$ $r$ $c$ $\oslash$ $S$ Kind Mode NPs EPs gt GraphML GML csv
correspsearch_v2 16,731 130,104 7.78 219.15 22.71 1304.33 -0.34 0.05 17 0.96 Directed Unipartite name uri type gender birth death gnd viaf wikidata date_from date_to label place_from place_to latitude_from longitude_from latitude_to longitude_to source 2.3 MiB 2.8 MiB 2.8 MiB 3.4 MiB
correspsearch_v1 16,745 130,104 7.77 219.06 22.66 1306.64 -0.34 0.05 17 0.96 Directed Unipartite name uri type gender birth death gnd viaf wikidata date_from date_to label place_from place_to latitude_from longitude_from latitude_to longitude_to source 2.3 MiB 2.8 MiB 2.8 MiB 3.3 MiB
finland 107,172 1,283,361 11.97 223.97 73.49 1576.36 -0.14 0.13 17 0.96 Directed Unipartite name uri type gender birth death sent_letters received_letters date_from date_to label source fonds 13.6 MiB 16.2 MiB 15.7 MiB 18.3 MiB
Ridiculograms*
* These are automatically generated force-directed visualizations, and can be quite meaningless for networks both big and small. They should not be taken seriously as sources of scientific insight. See here for a discussion.