Network, Popularity and Social Cohesion: A Game-Theoretic Approach
Authors: Jiamou Liu, Ziheng Wei
AAAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We evaluate the heuristics on graphs of size n = 5, . . . , 18. For each n = 8, . . . , 18, we generate 105 Erd os-Reny ı random graphs of size n. As shown in Fig. 2(a), both heuristics achieve high accuracy. We further evaluate the heuristics on 8 real-world networks |
| Researcher Affiliation | Academia | Jiamou Liu, Ziheng Wei The University of Auckland Department of Computer Science Auckland, New Zealand jiamou.liu@auckland.ac.nz z.wei@auckland.ac.nz |
| Pseudocode | Yes | Algorithm 1 Construction of H given G=(V, E) and k>2; Algorithm 2 AP: Given a network G = (V, E) |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described in this paper. |
| Open Datasets | Yes | For each n = 8, . . . , 18, we generate 105 Erd os-Reny ı random graphs of size n. We further evaluate the heuristics on 8 real-world networks: karate club ZA (Zachary 1977), dolphins DO (Lusseau et al. 2003), college football FT (Girvan and Newman 2002), Facebook FB, Enron email network EN (Leskovec et al. 2009), and three physics collaboration networks AS, CM and HE (Leskovec et al. 2007). |
| Dataset Splits | No | The paper does not provide specific dataset split information (exact percentages, sample counts, citations to predefined splits, or detailed splitting methodology) needed to reproduce the data partitioning. |
| Hardware Specification | No | The paper does not provide specific hardware details (exact GPU/CPU models, processor types with speeds, memory amounts, or detailed computer specifications) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details (e.g., library or solver names with version numbers) needed to replicate the experiment. |
| Experiment Setup | No | The paper does not contain specific experimental setup details (concrete hyperparameter values, training configurations, or system-level settings) in the main text. |