Dataset of networks used in assessing the Troika algorithm for clique partitioning and community detection
This dataset contains real and randomly generated networks (random graphs) from a study on clique partitioning. In total, there are 145 network files. This includes five categories: 27 ABCD graphs, 20 LFR graphs, 53 real networks, 20 Barabasi-Albert graphs, and 25 portfolio networks (S&P 500) as described in the article linked below this description. The folders describe the five categories of the networks. Each network is provided in .gml format or .pkl format which can be read into a networkX graph object using standard functions from the networkX library in Python. For accessing other networks used in the study, please refer to the article for references to the primary sources of those network data.
This dataset is provided under a CC BY-NC-SA Creative Commons v 4.0 license (Attribution-NonCommercial-ShareAlike). This means that other individuals may remix, tweak, and build upon these data non-commercially, as long as:
1) They provide citations to this data repository (https://doi.org/10.6084/m9.figshare.28835837) and the reference article listed below;
2) They license the new creations under the identical terms.
For more information about the data, one may refer to the article below:
Samin Aref and Boris Ng. "Troika algorithm: approximate optimization for accurate clique partitioning and clustering of weighted networks." arXiv preprint (2025).
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- Complex systems
- Information systems not elsewhere classified
- Optimisation
- Operations research
- Social and community informatics
- Numerical and computational mathematics not elsewhere classified
- Data structures and algorithms
- Statistical mechanics, physical combinatorics and mathematical aspects of condensed matter