Synthie (Labeled Networks)
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This network dataset is in the category of Labeled Networks
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Metadata
| Category | Labeled Networks |
| Collection | Labeled Networks |
| Tags | |
| Short | Labeled Networks |
| Description | This network contains the following comma separated text files: |
| Synthie is a synthetic data sets consisting of 400 graphs. The data set is subdivided into four classes. Each node has a real-valued attribute vector of dimension 15 and no labels. We used the following procedure to generate the data set: First, we generated two Erdös-Rényi graphs using the G(n,p) model with p | 0.2 and n: 10. For each graph we generated a seed set S_i for i in {1,2 of 200 graphs by randomly adding or deleting 25% of the edges. From these seed sets we generated two classes C_1 and C_2 of 200 graphs each by randomly sampling 10 graphs from S_1 cup S_2 and randomly connecting these graphs. For C_1 we choose a seed graph with probability 0.8 from S_1 and with probability 0.2 from S_2. The class C_2 was generated the same way but with interchanged probabilities. Finally, we generated a set of real-valued vectors of dimension 15 subdivided into two classes A and B using the make_classification method Scikit-learn. We then subdivided C_i into two classes C^A_i and C^B_i by drawing a random attribute from A or B for each node. For class C^A_i, we drew an attribute from A if the node belonged to a seed graph of seed set S_1, and from B otherwise. Class C^B_i was created the same way but with interchanged seed sets. |
Please cite the following if you use the data:
Note that if you transform/preprocess the data, please consider sharing the data by uploading it along with the details on the transformation and reference to any published materials using it.
@inproceedings{nr,
title={The Network Data Repository with Interactive Graph Analytics and Visualization},
author={Ryan A. Rossi and Nesreen K. Ahmed},
booktitle={AAAI},
url={https://networkrepository.com},
year={2015}
}
Network Data Statistics
| Nodes | 36.6K |
| Edges | 161.7K |
| Density | 0.000240981 |
| Maximum degree | 48 |
| Minimum degree | 2 |
| Average degree | 8 |
| Assortativity | -0.171457 |
| Number of triangles | 125.8K |
| Average number of triangles | 3 |
| Maximum number of triangles | 68 |
| Average clustering coefficient | 0.0801794 |
| Fraction of closed triangles | 0.0615987 |
| Maximum k-core | 11 |
| Lower bound of Maximum Clique | 4 |
Network Data Preview
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Interactive Visualization of Node-level Properties and Statistics
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