Network Data - Network community detection via neural embeddings

This is the data repository for Kojaku et al.'s study, "Network community detection via neural embeddings," published in Nature Communications. It includes the following network data:

- **multi_partition_model**: Network generated by the stochastic block model.
- **lfr**: Lancichinetti-Fortunato-Radicchi networks.
- **empirical**: Empirical networks used in this study.

Each folder contains network data comprising two files: `node_*.npz` and `net_*.npz`. The `net_*.npz` file can be loaded as an adjacency matrix using `scipy.sparse.load_npz`. The `node_*.npz` file is a CSV containing the ground-truth community memberships of the nodes.

本数据集为Kojaku等人发表于《自然-通讯》（Nature Communications）的研究"基于神经嵌入的网络社区检测（Network community detection via neural embeddings）"配套的数据仓库。本数据集包含以下网络数据：

- **多分区模型（multi_partition_model）**：由随机块模型（stochastic block model）生成的网络。
- **LFR网络（lfr）**：兰契奇内蒂-福尔图纳托-拉迪基（Lancichinetti-Fortunato-Radicchi）网络。
- **实证数据集（empirical）**：本研究使用的实证网络。

每个文件夹均包含两类网络数据文件：`node_*.npz`与`net_*.npz`。其中，`net_*.npz`文件可通过`scipy.sparse.load_npz`加载为邻接矩阵；`node_*.npz`文件为CSV格式文件，存储了各节点的真实社区归属信息。