Heterogeneous Peer Effects in the Linear Threshold Model
Authors: Christopher Tran, Elena Zheleva4175-4183
AAAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our experimental results on synthetic and realworld datasets show that our proposed models can better predict individual-level thresholds in the Linear Threshold Model and thus more precisely predict which nodes will get activated over time. |
| Researcher Affiliation | Academia | Christopher Tran, Elena Zheleva Department of Computer Science, University of Illinois at Chicago Chicago, IL {ctran29, ezheleva}@uic.edu |
| Pseudocode | Yes | Pseudocode for ST-Learner is available in the Appendix. |
| Open Source Code | Yes | The proof is in the Appendix2. 2https://github.com/edgeslab/hpe-ltm |
| Open Datasets | Yes | The Hateful Users dataset is a retweet network from Twitter, with 200 most recent tweets for each user (Ribeiro et al. 2018). ... Higgs Boson. This dataset is based on the announcement of the Higgs-boson-like particle at CERN on July 4, 2012. ... (De Domenico et al. 2013). |
| Dataset Splits | No | The paper mentions 'training data' and refers to using 'a validation set' for the CT-HV method. However, it does not explicitly provide specific percentages, sample counts, or methodology for the train/validation/test splits of the datasets used in their experiments. |
| Hardware Specification | No | The paper does not provide specific hardware details such as GPU or CPU models used for running the experiments. |
| Software Dependencies | No | The paper does not list specific software dependencies with version numbers (e.g., Python, PyTorch versions). |
| Experiment Setup | Yes | We set the number of nodes to 1000, and for each node, we randomly generate 100 node attributes from a Gaussian, N(0, 1). ... 50 nodes are randomly activated, and diffusion events are generated based on LTM for 8 time steps. |