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The integrity of democratic elections depends on voters' access to accurate information. However, modern media environments, which are dominated by social media, provide malicious actors with unprecedented ability to manipulate elections…

Computer Science and Game Theory · Computer Science 2018-11-22 Bryan Wilder , Yevgeniy Vorobeychik

The Web Bulletin Board (WBB) is a key component of verifiable election systems. It is used in the context of election verification to publish evidence of voting and tallying that voters and officials can check, and where challenges can be…

Cryptography and Security · Computer Science 2014-01-17 Chris Culnane , Steve Schneider

Electronic voting consistently fails to supplant conventional paper ballot due to a plethora of security shortcomings. Not only are traditional voting methods mediocre in terms of convenience and interface, they also encompass…

Cryptography and Security · Computer Science 2026-04-29 Vitaly Zuevsky

How can voters induce politicians to put forth more proximate (in terms of preference) as well as credible platforms (in terms of promise fulfillment) under repeated elections? Building on the work of Aragones et al. (2007), I study how…

Theoretical Economics · Economics 2025-09-11 Shiladitya Kumar

We study computational questions in a game-theoretic model that, in particular, aims to capture advertising/persuasion applications such as viral marketing. Specifically, we consider a multi-agent Bayesian persuasion model where an informed…

Computer Science and Game Theory · Computer Science 2016-03-07 Yakov Babichenko , Siddharth Barman

We propose an efficient framework for enabling secure multi-party numerical computations in a Peer-to-Peer network. This problem arises in a range of applications such as collaborative filtering, distributed computation of trust and…

Cryptography and Security · Computer Science 2010-05-04 Danny Bickson , Tzachy Reinman , Danny Dolev , Benny Pinkas

We study online Bayesian persuasion problems in which an informed sender repeatedly faces a receiver with the goal of influencing their behavior through the provision of payoff-relevant information. Previous works assume that the sender has…

Computer Science and Game Theory · Computer Science 2024-11-12 Francesco Bacchiocchi , Matteo Bollini , Matteo Castiglioni , Alberto Marchesi , Nicola Gatti

Online advertising has motivated interest in online selection problems. Displaying ads to the right users benefits both the platform (e.g., via pay-per-click) and the advertisers (by increasing their reach). In practice, not all users click…

Computer Science and Game Theory · Computer Science 2024-08-16 Sebastian Perez-Salazar , Mohit Singh , Alejandro Toriello

Many voter-verifiable, coercion-resistant schemes have been proposed, but even the most carefully designed systems necessarily leak information via the announced result. In corner cases, this may be problematic. For example, if all the…

Cryptography and Security · Computer Science 2019-08-15 Wojciech Jamroga , Peter B. Roenne , Peter Y. A. Ryan , Philip B. Stark

The major finding, of this article, is an ensemble method, but more exactly, a novel, better ranked voting system (and other variations of it), that aims to solve the problem of finding the best candidate to represent the voters. We have…

Artificial Intelligence · Computer Science 2021-10-15 Gabriel-Claudiu Grama

Benaloh challenge allows the voter to audit the encryption of her vote, and in particular to check whether the vote has been represented correctly. An interesting analysis of the mechanism has been presented by Culnane and Teague. The…

Cryptography and Security · Computer Science 2023-10-19 Wojciech Jamroga

The legitimacy of bottom-up democratic processes for the distribution of public funds by policy-makers is challenging and complex. Participatory budgeting is such a process, where voting outcomes may not always be fair or inclusive.…

Multiagent Systems · Computer Science 2023-07-25 Srijoni Majumdar , Evangelos Pournaras

The law forbids discrimination. But the ambiguity of human decision-making often makes it extraordinarily hard for the legal system to know whether anyone has actually discriminated. To understand how algorithms affect discrimination, we…

Computers and Society · Computer Science 2019-02-12 Jon Kleinberg , Jens Ludwig , Sendhil Mullainathan , Cass R. Sunstein

When subjected to automated decision-making, decision subjects may strategically modify their observable features in ways they believe will maximize their chances of receiving a favorable decision. In many practical situations, the…

Computer Science and Game Theory · Computer Science 2022-10-10 Keegan Harris , Valerie Chen , Joon Sik Kim , Ameet Talwalkar , Hoda Heidari , Zhiwei Steven Wu

We study voting games on binary issues, where voters hold an objective over the outcome of the collective decision and are allowed, before the vote takes place, to negotiate their voting strategy with the other participants. We analyse the…

Computer Science and Game Theory · Computer Science 2017-01-10 Umberto Grandi , Davide Grossi , Paolo Turrini

We study computational aspects of three prominent voting rules that use approval ballots to elect multiple winners. These rules are satisfaction approval voting, proportional approval voting, and reweighted approval voting. We first show…

Computer Science and Game Theory · Computer Science 2014-07-14 Haris Aziz , Serge Gaspers , Joachim Gudmundsson , Simon Mackenzie , Nicholas Mattei , Toby Walsh

Purpose: Multiwinner voting rules typically require full knowledge of voter preferences, which becomes impractical in large-scale or attention-limited settings. This paper investigates how accurately a winning committee can be approximated…

Computer Science and Game Theory · Computer Science 2026-04-01 Itay Asher Zimet , Shiri Alouf-Heffetz , Nimrod Talmon

In this paper we introduce the hiring under uncertainty problem to model the questions faced by hiring committees in large enterprises and universities alike. Given a set of $n$ eligible candidates, the decision maker needs to choose the…

Data Structures and Algorithms · Computer Science 2019-05-08 Manish Raghavan , Manish Purohit , Sreenivas Gollupadi

How should we decide which fairness criteria or definitions to adopt in machine learning systems? To answer this question, we must study the fairness preferences of actual users of machine learning systems. Stringent parity constraints on…

Artificial Intelligence · Computer Science 2020-12-09 Angie Peng , Jeff Naecker , Ben Hutchinson , Andrew Smart , Nyalleng Moorosi

This work analyses surprising elections, and attempts to quantify the notion of surprise in elections. A voter is surprised if their estimate of the winner (assumed to be based on a combination of the preferences of their social connections…

Social and Information Networks · Computer Science 2018-11-26 Sagar Massand , Swaprava Nath
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