We lifted 6 functions out of this paper's own repositories and ran 5 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| shobrook/communities | reimplementation | 5 of 6 |
| Function | Status | Where it lives |
|---|---|---|
| animation_data | Ran | shobrook/communities/communities/algorithms/girvan_newman.py code served (permissive licence) · get_code("3ec16b5044ac29e8") |
| get_all_edges | Ran | shobrook/communities/communities/algorithms/louvain_method.py code served (permissive licence) · get_code("638070cebea66a0c") |
| initialize_node_to_comm | Ran | shobrook/communities/communities/algorithms/louvain_method.py code served (permissive licence) · get_code("28ad853f0afe6c69") |
| invert_node_to_comm | Ran | shobrook/communities/communities/algorithms/louvain_method.py code served (permissive licence) · get_code("3d3c93947c899e96") |
| prune_edges | Ran | shobrook/communities/communities/algorithms/girvan_newman.py code served (permissive licence) · get_code("2481ea9230ba764c") |
| girvan_newman | Not yet run | shobrook/communities/communities/algorithms/girvan_newman.py code served (permissive licence) · get_code("16f7a1dc609c07a8") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
We propose a simple method to extract the community structure of large networks. Our method is a heuristic method that is based on modularity optimization. It is shown to outperform all other known community detection method in terms of computation time. Moreover, the quality of the communities detected is very good, as measured by the so-called modularity. This is shown first by identifying language communities in a Belgian mobile phone network of 2.6 million customers and by analyzing a web graph of 118 million nodes and more than one billion links. The accuracy of our algorithm is also verified on ad-hoc modular networks. .
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("0803.0476")
get_code_for_paper("0803.0476")
have("0803.0476")
Connect an agent — have() is free.