Nimrod Talmon

Pairwise Liquid Democracy

In a liquid democracy, voters can either vote directly or delegate their vote to another voter of their choice. We consider ordinal elections, and study a model of liquid democracy in which voters specify partial orders and use several delegates to refine them. This flexibility, however, comes at a price, as individual rationality (in the form of transitive preferences) can no longer be guaranteed. We discuss ways to detect and overcome such complications. Based on the framework of distance rationalization, we introduce novel variants of voting rules that are tailored to the liquid democracy context.

Opinion Diffusion and Campaigning on Society Graphs

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. Moreover, we report on certain computational simulations.

Egalitarian Committee Scoring Rules

We introduce and study the class of egalitarian variants of committee scoring rules, where instead of summing up the scores that voters assign to committees—as is done in the utilitarian variants— the score of a committee is taken to be the lowest score assigned to it by any voter. We focus on five rules, which are egalitarian analogues of SNTV, the k-Borda rule, the Chamberlin–Courant rule, the Bloc rule, and the Pessimist rule. We establish their computational complexity, provide their initial axiomatic study, and perform experiments to represent the action of these rules graphically.

Can We Create Large k -Cores by Adding Few Edges?

The notion of a k-core, defined by Seidman [’83], has turned out to be useful in analyzing network structures. The k-core of a given simple and undirected graph is the maximal induced subgraph such that each vertex in it has degree at least k. Hence, finding a k-core helps to identify a (core) community where each entity is related to at least k other entities. One can find the k-core of a given graph in polynomial time, by iteratively deleting each vertex of degree less than k. Unfortunately, this iterative dropping out of vertices can sometimes lead to unraveling of the entire network; e.g., Schelling [’78] considered the extreme example of a path with (k = 2), where indeed the whole network unravels.