Opinion Dynamics with Local Interactions
Authors: Dimitris Fotakis, Dimitris Palyvos-Giannas, Stratis Skoulakis
IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our experimental findings indicate that for a wide range of parameters, the convergence time and the number of opinion clusters of the neighborhood-restricted variants are comparable to those of the standard Hegselmann-Krause model. |
| Researcher Affiliation | Academia | Dimitris Fotakis and Dimitris Palyvos-Giannas and Stratis Skoulakis National Technical University of Athens fotakis@cs.ntua.gr, dpalyvos@corelab.ntua.gr, sskoul@corelab.ntua.gr |
| Pseudocode | No | No pseudocode or algorithm blocks were found. |
| Open Source Code | No | No explicit statement or link for open-source code for the described methodology was found. |
| Open Datasets | Yes | Finally, we test the network-HK model on the Facebook circles network [Leskovec, 2012], with 4039 nodes and 88234 edges (see Figure 6a). |
| Dataset Splits | No | The paper does not provide specific train/test/validation dataset splits. |
| Hardware Specification | No | No specific hardware (GPU/CPU models, memory, etc.) used for running experiments is mentioned. |
| Software Dependencies | No | No specific software dependencies with version numbers were mentioned. |
| Experiment Setup | Yes | We simulate the random-HK and the standard HK models for 625 agents and 21 values of " \in [.01, .45], repeating each run for 100 different initial opinion vectors to account for the randomness in local interaction. Opinions are selected uniformly at random from [0, 1] in all our simulations. We choose k = min(n/10, log n/") to ensure that with high probability every agent has some neighbors in each cluster. |