DyNMF: Role Analytics in Dynamic Social Networks
Authors: Yulong Pei, Jianpeng Zhang, George Fletcher, Mykola Pechenizkiy
IJCAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments on both synthetic and real-world SNs demonstrate the advantages of Dy NMF in discovering and predicting roles and role transitions. |
| Researcher Affiliation | Academia | Yulong Pei, Jianpeng Zhang, George Fletcher, Mykola Pechenizkiy Eindhoven University of Technology, the Netherlands |
| Pseudocode | Yes | Algorithm 1 Optimization Algorithm |
| Open Source Code | No | The paper does not provide any explicit statement about open-sourcing code or a link to a code repository for the methodology described. |
| Open Datasets | Yes | To validate the advantages of our proposed Dy NMF for role discovery and role transition learning, we conduct experiments on one synthetic data set and four real-world data sets. ... networkrepository.com/index.php |
| Dataset Splits | No | The paper mentions 'train', 'validation', and 'test' in the schema but does not provide specific dataset split information (percentages, counts, or predefined splits) for reproducing its experiments. |
| Hardware Specification | No | The paper does not provide specific hardware details (like GPU/CPU models, processor types, or memory) used for running its experiments. |
| Software Dependencies | No | The paper mentions several methods and algorithms but does not provide specific version numbers for any software dependencies or libraries used in the implementation of Dy NMF or the experiments. |
| Experiment Setup | No | The paper mentions some general settings like using 'multiplicative update rules' until 'convergence (or the number of iteration exceeds a given threshold)' and a 'fixed change rate' for synthetic data. However, it does not provide concrete hyperparameter values or detailed training configurations (e.g., specific learning rates, batch sizes, or explicit iteration thresholds) in the main text. |