Putting a Compass on the Map of Elections
Authors: Niclas Boehmer, Robert Bredereck, Piotr Faliszewski, Rolf Niedermeier, Stanisław Szufa
IJCAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We use them to analyze both a dataset provided by Szufa et al. and a number of real-life elections. |
| Researcher Affiliation | Academia | Niclas Boehmer1 , Robert Bredereck2 , Piotr Faliszewski3 , Rolf Niedermeier1 and Stanisław Szufa4 1Algorithmics and Computational Complexity, TU Berlin, Germany 2Humboldt-Universit at zu Berlin, Germany 3AGH University, Poland 4Jagiellonian University, Poland |
| Pseudocode | No | The paper describes algorithms (e.g., for EMD and recovering elections from matrices), but it does not present them in a structured pseudocode or algorithm block format. |
| Open Source Code | No | The paper states 'We provide details missing from this paper in its full version, available as a technical report [Boehmer et al., 2021].' but it does not provide a direct link or explicit statement about the open-sourcing of the code for the methodology described in this paper. |
| Open Datasets | Yes | We use them to analyze both a dataset provided by Szufa et al. and a number of real-life elections. ... datasets that we use (mostly from Pref Lib, due to Mattei and Walsh [2013]). |
| Dataset Splits | No | The paper describes analyzing datasets and real-life elections to understand their properties and positions on a map, but it does not mention or specify any training, validation, or test dataset splits for its experiments. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware (e.g., CPU, GPU models, memory, or cloud instances) used to conduct its experiments or computations. |
| Software Dependencies | No | The paper mentions using a 'force-directed algorithm of Fruchterman and Reingold [1991]' and 'ILPs,' but it does not specify any software libraries, packages, or solvers with version numbers that would be necessary to replicate the work. |
| Experiment Setup | Yes | We consider their dataset with 10 candidates and 100 voters (see Figure 1 for its map). ... To generate an urn election, we choose α according to the Gamma distribution with shape parameter k = 0.8 and scale parameter θ = 1... In Figures 3c and 3d we visualize Mallows elections generated with φ [0, 1] and relφ [0, 0.5] chosen uniformly at random, respectively (we use rel-φ 0.5 because for larger values one obtains analogous elections, but reversed; e.g., both rel-φ = 0 and rel-φ = 1 lead to identity elections). |