Network Embeddings DeepWalk 2020-2022

DOI

This dataset contains network embeddings of all individuals who are registered in the Basisregistratie Personen (BRP) on January 1st YYYY and part of at least one population network file, i.e., BURENNETWERKYYYYTAB, COLLEGANETWERKYYYYTAB, FAMILIENETWERKYYYYTAB, HUISGENOTENNETWERKYYYYTAB, KLASGENOTENNETWERKYYYYTAB. All network datasets from the same year were concatenated and duplicate relations between every pair of individuals removed. The network was made symmetric by adding missing reciprocal relations. The resulting undirected and unweighted network was used to create the embeddings. Network embeddings are numerical representations with a fixed number of dimensions that encode the position of an individual in the network. The embeddings in this dataset were created using the DeepWalk algorithm and have 32, 64, or 128 dimensions. The DeepWalk algorithm samples node sequences (random walks) from a network and creates embeddings by training a Skip-gram model to predict nodes in each sequence from a context window. The embeddings in this dataset were created using 100 sequences of length 20 starting at each node in the network. The size of the context window was 5. The SkipGram model was trained for 2 epochs, that is, each sequence was iterated over twice. The dataset files follow the schema NETEMBEDDEEPWALKYYYYDIMXXX where DIMXXX refers to the number of dimensions.

This dataset is only available under strict conditions within the Microdata Environment at CBS. Since this is a project-generated dataset made available for reuse via the CBS Data Storage, access to the following source CBS files has to be requested:

Burennetwerk    2020-2022
Colleganetwerk  2020-2022
Familienetwerk  2020-2022
Huisgenotennetwerk  2020-2022
Klasgenotennetwerk  2020-2022

(see full list under "Data Source"). Read more about the conditions to access and use the CBS data: www.cbs.nl/nl-nl/onze-diensten/maatwerk-en-microdata/microdata-zelf-onderzoek-doen.

The dataset contains the following variables:

RINPERSOONS: Samen met RINPERSOON identificeert dit nummer de persoon (String): De bron waaruit een persoon identificerend nummer is afgeleid RINPERSOON: Samen met RINPERSOONS identificeert dit nummer de persoon (String): Dit nummer identificeert een natuurlijk persoon. Het is een betekenis- en dimensieloos nummer. DIMXXX: Embedding dimension XXX (Numeric): Abstract number that encodes an individuals position in the network. The number can be positive or negative and is centered around zero. The dataset can contain between 32 and 128 columns of this type.

Identifier
DOI https://doi.org/10.34894/VRNLKJ
Metadata Access https://dataverse.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34894/VRNLKJ
Provenance
Creator Lüken, Malte (ORCID: 0000-0001-7095-203X); Garcia-Bernardo, Javier ORCID logo; Deb, Sreeparna ORCID logo; Hafner, Fabio ORCID logo; Khosla, Megha
Publisher DataverseNL
Contributor Lüken, Malte; Khosla, Megha; ODISSEI; TU Delft; Netherlands eScience Center; Centraal Bureau voor Statistiek (CBS)
Publication Year 2025
Rights info:eu-repo/semantics/openAccess
OpenAccess true
Contact Lüken, Malte (esciencecenter.nl); Khosla, Megha (tudelft.nl)
Representation
Resource Type Dataset
Version 1.0
Discipline Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Business and Management; Economics; Life Sciences; Medicine; Social Sciences; Social and Behavioural Sciences; Soil Sciences