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We show that a simple model for the propagation of a rumor on a small-world network exhibits critical behavior at a finite randomness of the underlying graph. The transition occurs between a regime where the rumor "dies" in a small…

Statistical Mechanics · Physics 2007-05-23 Damian H. Zanette

We provide a systematic study of the problem of finding the source of a rumor in a network. We model rumor spreading in a network with a variant of the popular SIR model and then construct an estimator for the rumor source. This estimator…

Machine Learning · Statistics 2010-11-03 Devavrat Shah , Tauhid Zaman

In this paper we study a rational inattention model in environments where the decision maker faces uncertainty about the true prior distribution over states. The decision maker seeks to select a stochastic choice rule over a finite set of…

Theoretical Economics · Economics 2023-05-08 Emerson Melo

The standard central limit theorem with a Gaussian attractor for the sum of independent random variables may lose its validity in presence of strong correlations between the added random contributions. Here, we study this problem for…

Statistical Mechanics · Physics 2016-06-14 Adrian A. Budini

We study the asymptotic macroscopic properties of the mixed majority-minority game, modeling a population in which two types of heterogeneous adaptive agents, namely ``fundamentalists'' driven by differentiation and ``trend-followers''…

Statistical Mechanics · Physics 2009-11-10 A. De Martino , I. Giardina , G. Mosetti

The influence of contrarians on the noisy voter model is studied at the mean-field level. The noisy voter model is a variant of the voter model where agents can adopt two opinions, optimistic or pessimistic, and can change them by means of…

Physics and Society · Physics 2018-10-10 Nagi Khalil , Raul Toral

We develop a theory of estimation when in addition to a sample of $n$ observed outcomes the underlying probabilities of the observed outcomes are known, as is typically the case in the context of numerical simulation modeling, e.g. in…

Methodology · Statistics 2023-04-14 Jobst Heitzig

We explore uncertainty quantification in large language models (LLMs), with the goal to identify when uncertainty in responses given a query is large. We simultaneously consider both epistemic and aleatoric uncertainties, where the former…

Machine Learning · Computer Science 2024-07-18 Yasin Abbasi Yadkori , Ilja Kuzborskij , András György , Csaba Szepesvári

An asymmetric information model is introduced for the situation in which there is a small agent who is more susceptible to the flow of information in the market than the general market participant, and who tries to implement strategies…

Trading and Market Microstructure · Quantitative Finance 2013-01-31 Dorje C. Brody , Mark H. A. Davis , Robyn L. Friedman , Lane P. Hughston

The principle of rewarding a crowd for surprisingly common answers has been used in the literature for designing a number of truthful information elicitation mechanisms. A related method has also been proposed in the literature for better…

Machine Learning · Computer Science 2025-01-28 Naman Goel

This paper develops a qualitative framework for analysing the impact of rumours on complex investment decisions (CID) under severe information constraints. The proposed trend-based models rely on minimal data inputs in the form of…

General Economics · Economics 2025-09-03 Nina Bočková , Karel Doubravský , Barbora Volná , Mirko Dohnal

Several Artificial Intelligence schemes for reasoning under uncertainty explore either explicitly or implicitly asymmetries among probabilities of various states of their uncertain domain models. Even though the correct working of these…

Artificial Intelligence · Computer Science 2013-02-28 Marek J. Druzdzel

We adapt arguments concerning information-theoretic convergence in the Central Limit Theorem to the case of dependent random variables under Rosenblatt mixing conditions. The key is to work with random variables perturbed by the addition of…

Probability · Mathematics 2008-10-06 Oliver Johnson

This paper models information diffusion in a network of Large Language Models (LLMs) that is designed to answer queries from distributed datasets, where the LLMs can hallucinate the answer. We introduce a two-time-scale dynamical model for…

Social and Information Networks · Computer Science 2025-04-22 Adit Jain , Vikram Krishnamurthy , Yiming Zhang

The bounded confidence model of opinion dynamics, introduced by Deffuant et al, is a stochastic model for the evolution of continuous-valued opinions within a finite group of peers. We prove that, as time goes to infinity, the opinions…

Probability · Mathematics 2011-04-19 Javier Gómez-Serrano , Carl Graham , Jean-Yves Le Boudec

Information and uncertainty are closely related and extensively studied concepts in a number of scientific disciplines such as communication theory, probability theory, and statistics. Increasing the information arguably reduces the…

Probability · Mathematics 2011-08-09 Jiahua Chen

We propose and analyze a quasirandom analogue of the classical push model for disseminating information in networks ("randomized rumor spreading"). In the classical model, in each round each informed vertex chooses a neighbor at random and…

Data Structures and Algorithms · Computer Science 2015-03-17 Benjamin Doerr , Tobias Friedrich , Thomas Sauerwald

When opinions, behaviors or ideas diffuse within a population, some are invariably stickier than others. The stickier the opinion, behavior or idea, the greater is an individual's inertia to replace it with an alternative. Here we study the…

Physics and Society · Physics 2015-12-02 C. Doyle , S. Sreenivasan , B. K. Szymanski , G. Korniss

In the era of the rapid development of the Internet, the threshold for information spreading has become lower. Most of the time, rumors, as a special kind of information, are harmful to society. And once the rumor appears, the truth will…

Social and Information Networks · Computer Science 2021-01-27 Yan Wang , Feng Qing , Jian-Ping Chai , Ye-Peng Ni

In this paper, we consider a random network such that there could be a link between any two nodes in the network with a certain probability (plink). Diffusion is the phenomenon of spreading information throughout the network, starting from…

Social and Information Networks · Computer Science 2015-11-23 Natarajan Meghanathan