Uncovering the Largest Community in Social Networks at Scale
Authors: Shohei Matsugu, Yasuhiro Fujiwara, Hiroaki Shiokawa
IJCAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | 4 Experimental Evaluation We experimentally evaluated the efficiency of Bn M. |
| Researcher Affiliation | Collaboration | Shohei Matsugu1 , Yasuhiro Fujiwara2 and Hiroaki Shiokawa3 1Graduate School of Science and Technology, University of Tsukuba, Japan 2NTT Communication Science Laboratories, Japan 3Center for Computational Sciences, University of Tsukuba, Japan |
| Pseudocode | Yes | Algorithm 1 Node-merging algorithm... Algorithm 2 Proposed method: Branch-and-Merge (Bn M) |
| Open Source Code | No | The paper does not provide a specific link or explicit statement about the open-source availability of the code for the described methodology. |
| Open Datasets | Yes | We tested 11 real-world social networks used in previous works [Gao et al., 2018; Zhou et al., 2021; Jiang et al., 2021; Chang et al., 2022] with more than 100,000 nodes, which are originally published by the Network Repository [Rossi and Ahmed, 2015]2. 2All graphs are publicly available online from https://networkrepository.com. |
| Dataset Splits | No | The paper does not provide specific details on dataset splits (e.g., train/validation/test percentages or counts) or reference standard predefined splits. |
| Hardware Specification | Yes | All experiments were conducted on a Linux server with Intel Xeon Gold 6246R CPU 3.40 GHz and 128 Gi B RAM. |
| Software Dependencies | No | The paper mentions "implemented in C/C++ using -O3 option" but does not specify versions for any ancillary software, libraries, or solvers. |
| Experiment Setup | Yes | All experiments were conducted on a Linux server with Intel Xeon Gold 6246R CPU 3.40 GHz and 128 Gi B RAM. All algorithms were implemented in C/C++ using -O3 option as a single-threaded program with the entire graph held in the main memory. Similar to previous studies [Gao et al., 2018; Zhou et al., 2021], we varied k from 2 to 5. |