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This repository has been archived by the owner on Oct 26, 2024. It is now read-only.

👾 extraction and analysis of several graph (complex networks) features from publicly available datasets with NetworkX

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autistic-symposium/ml-graph-network-analyser-py

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ml-graph-network-analyser


👉 this project contains the source code for the extraction and analysis of several graph (complex networks) features from publicly available datasets with NetworkX



analyzed features


  • assortativity
  • clique number
  • clustering
  • density
  • diameter
  • edge connectivity
  • node connectivity
  • number of cliques
  • number of edges
  • number of nodes
  • radius
  • clustering and transitivity
  • betweenness centrality
  • closeness centrality
  • communicability centrality
  • coreness
  • degree centrality
  • eccentricity
  • number of triangles
  • pagerank
  • square clustering
  • transitivity


analyzed networks


  • social networks: online social networks, edges represent interactions between people
  • ground truth: ground-truth network communities in social and information networks
  • communication: email communication networks with edges representing communication
  • citation: nodes represent papers, edges represent citations
  • collaboration: nodes represent scientists, edges represent collaborations (co-authoring a paper)
  • web graphs: nodes represent webpages and edges are hyperlinks
  • products: nodes represent products and edges link commonly co-purchased products
  • p2p: nodes represent computers and edges represent communication
  • roads: nodes represent intersections and edges roads connecting the intersections
  • autonomous systems: graphs of the internet
  • signed networks: networks with positive and negative edges (friend/foe, trust/distrust)
  • location-based networks: Social networks with geographic check-ins
  • wikipedia: yalk, editing and voting data from Wikipedia
  • bio atlas: food-webs selected from the ecosystem network analysis resources
  • bio-cellular: substrate in the cellular network of the corresponding organism
  • bio-metabolic: metabolic network of the corresponding organisms
  • bio-carbon: carbon exchanges in the cypress wetlands of south florida during the wet and dry season
  • bio yeast: protein-protein interaction network in budding yeast


additional considerations


normalization and graph sampling

  • performed using snowball sampling (choosing the sample order, i.e., number of nodes)
  • optimized for the number of edges and multiple samplings

next steps in the data pipeline