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Dataset of Visualization of Dynamic Graphs

We provided three distribution functions (e.g., Gaussian distribution, Poisson distribution and random distribution) to simulate the time intervals for updating (insertion of new nodes and edges) the graphs.

Moreover, we selected three datasets with varying size, temporal edges and duration of time interval in the dataset.

  1. Dataset email-Eu-core-temporalDept3 (*) is an incoming and outgoing traffic for E-Mail graph. A separate edge is created for each recipient of the e-mail.
  2. Dataset CollegeMsg (**) is a temporal graph comprised of private messages sent on an online social network at the University of California.
  3. Dataset soc-sign-bitcoinalpha (***) is a transaction graph in BitCoin Alpha.
  • (*) Paranjape, Ashwin, Austin R. Benson, and Jure Leskovec. “Motifs in temporal networks.” Proceedings of the Tenth ACM International Conference on Web Search and Data Mining. 2017.
  • (**) Panzarasa, Pietro, Tore Opsahl, and Kathleen M. Carley. “Patterns and dynamics of users’ behavior and interaction: Network analysis of an online community.” Journal of the American Society for Information Science and Technology 60.5 (2009): 911-932.
  • (***) Kumar, Srijan, et al. “Edge weight prediction in weighted signed networks.” 2016 IEEE 16th International Conference on Data Mining (ICDM). IEEE, 2016.

Each distribution contains static (the name of folder ends with static) and dynamic datasets (the name of folder ends with dynamic):

Each dataset contains a time_span file (the time intervals for updating the graphs) and graph files. The data structure of graph file is the same as the Dataset of CNCAH Network.

Download:

  1. Gaussian Distribution (22.17 GB after extraction, 554,288 files)
  2. Poisson Distribution (11.08 GB after extraction, 277,144 files)
  3. Random Uniform Distribution (11.00 GB after extraction, 277,144 files)

If you use the dataset for your research/development, please cite the following paper:

Cheong, Se-Hang, Yain-Whar Si, and Raymond K. Wong. "Online force-directed algorithms for visualization of dynamic graphs." Information Sciences 556 (2021): 223-255.