Network Embeddings LINE DINE 2020-2022

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 LINE algorithm and have 16, 32, or 48 dimensions. The algorithm predicts whether two nods are connected in the network or randomly paired. It was trained for 5 epochs, i.e., it iterated over all relations in the network 5 times. The first half of the dimensions (i.e., dimensions 0-7, 0-15, and 0-23) contain first order embeddings reflecting location in the network. The second half contains second order embeddings reflecting similarity in local neighbourhood. The embeddings in this dataset were transformed using the DINE algorithm that forces the embedding dimensions to become more sparse and more orthogonal to each other. The dataset files follow the schema NETEMBEDLINEDINEYYYYDIMXXX where DIMXXX refers to the number of dimensions.