Opinion Diffusion and Campaigning on Society Graphs
Authors: Piotr Faliszewski, Rica Gonen, Martin Koutecký, Nimrod Talmon
IJCAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We study the effects of campaigning, where the society is partitioned into voter clusters and a diffusion process propagates opinions in a network connecting the clusters. Our model is very powerful and can incorporate many campaigning actions, various partitions of the society into clusters, and very general diffusion processes. Perhaps surprisingly, we show that computing the cheapest campaign for rigging a given election can usually be done efficiently, even with arbitrarily-many voters. The paper presents theorems, proofs, and uses integer linear programming (ILP) to demonstrate computational tractability, which are characteristics of theoretical research. |
| Researcher Affiliation | Academia | AGH University of Science and Technology, Krakow, Poland The Open University of Israel Technion Israel Institute of Technology, Haifa, Israel Charles University, Prague, Czech Republic Ben-Gurion University, Be er Sheva, Israel |
| Pseudocode | No | The paper presents mathematical constraints (Figure 3) which are part of an ILP formulation, but it does not include pseudocode or an algorithm block describing a step-by-step procedure. |
| Open Source Code | No | The paper does not provide any explicit statements about releasing source code or links to a code repository. |
| Open Datasets | No | The paper is theoretical and does not describe the use of any specific datasets for training or evaluation. |
| Dataset Splits | No | The paper is theoretical and does not describe any dataset splits for validation or other experimental purposes. |
| Hardware Specification | No | The paper is theoretical and does not describe any specific hardware used for experiments. |
| Software Dependencies | No | The paper refers to using Integer Linear Programming (ILP) and mentions a reference for standard tricks to linearize constraints, but does not specify any particular software, solver, or version (e.g., CPLEX, Gurobi) used. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup details such as hyperparameters or system-level training settings. |