Fatemeh Salehi Rizi and Michael Granitzer. "Properties of vector embeddings in social networks." Algorithms 10, no. 4 (2017): 109.

Properties of Vector Embeddings in Social Networks

The presented work was developed within the Provenance Analytics project funded by the German Federal Ministry of Education and Research, grant agreement number 03PSIPT5C.

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1. Learn embeddings using Deepwalk, node2vec or HARP
   
2. Give a ranking label to each pair of nodes by prepare_labels.py
   
3. Run RankSVM.py to learn weights for each graph property