Ballot Length in Instant Runoff Voting
Authors: Kiran Tomlinson, Johan Ugander, Jon Kleinberg
AAAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Finally, we analyze a collection of 168 real-world elections, where we truncate rankings to simulate shorter ballots. We find that shorter ballots could have changed the outcome in one quarter of these elections. |
| Researcher Affiliation | Academia | 1Cornell University 2Stanford University kt@cs.cornell.edu, jugander@stanford.edu, kleinberg@cornell.edu |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | Yes | Our code and data are available at https://github.com/tomlinsonk/irv-ballot-length. |
| Open Datasets | Yes | Finally, we use data from 168 real-world elections from Pref Lib (Mattei and Walsh 2013) |
| Dataset Splits | No | The paper analyzes real-world election data and simulated profiles, but does not describe traditional training/validation/test dataset splits for model development. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., exact GPU/CPU models, memory amounts) 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 | Yes | For the general profiles, we fix 1000 voters. For 1-Euclidean profiles, we simulate an infinite voter population uniformly distributed over [0, 1], where the number of first-place votes a candidate i has is the size of the interval of [0, 1] containing points closer to i than any other candidate. |