Publications associées à Croyance

Biases in Information Selection and Processing: Survey Evidence from the Pandemic

We conduct two survey experiments to study which information people choose to consume and how it affects their beliefs. In the first experiment, respondents choose between optimistic and pessimistic article headlines related to the COVID-19 pandemic and ar ...

2024

United States politicians' tone became more negative with 2016 primary campaigns

Robert West, Andreas Oliver Spitz, Ahmad Abu-Akel

There is a widespread belief that the tone of political debate in the US has become more negative recently, in particular when Donald Trump entered politics. At the same time, there is disagreement as to whether Trump changed or merely continued previous t ...

Nature Portfolio2023

A taxonomy of surprise definitions

Wulfram Gerstner, Johanni Michael Brea, Alireza Modirshanechi

Surprising events trigger measurable brain activity and influence human behavior by affecting learning, memory, and decision-making. Currently there is, however, no consensus on the definition of surprise. Here we identify 18 mathematical definitions of su ...

2022

End-to-End Task-Oriented Dialog Modeling With Semi-Structured Knowledge Management

Antoine Bosselut, Silin Gao

Current task-oriented dialog (TOD) systems mostly manage structured knowledge (e.g. databases and tables) to guide the goal-oriented conversations. However, they fall short of handling dialogs which also involve unstructured knowledge (e.g. reviews and doc ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Belief Control Strategies for Interactions Over Weakly-Connected Graphs

Ali H. Sayed, Bicheng Ying

In diffusion social learning over weakly-connected graphs, it has been shown recently that influential agents shape the beliefs of non-influential agents. This paper analyzes this mechanism more closely and addresses two main questions. First, the article ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Social Learning With Partial Information Sharing

Ali H. Sayed, Virginia Bordignon

This work studies the learning abilities of agents sharing partial beliefs over social networks. The agents observe data that could have risen from one of several hypotheses and interact locally to decide whether the observations they are receiving have ri ...

IEEE2020

Exponential Collapse Of Social Beliefs Over Weakly-Connected Heterogeneous Networks

Ali H. Sayed, Augusto José Rabelo Almeida Santos

We consider a distributed social learning problem where a network of agents is interested in selecting one among a finite number of hypotheses. The data collected by the agents might be heterogeneous, meaning that different sub-networks might observe data ...

IEEE2019

Intensive travel time: an obligation or a choice?

Stéphanie Vincent

This paper explores what prompts some individuals to spend a significant amount of time travelling. In the literature, travel time tends to be regarded as useless, unproductive time and, in some cases, as the worst time of the day. The actual behaviour of ...

Springer2016

Incentives for Truthful Information Elicitation of Continuous Signals

Boi Faltings, Goran Radanovic

We consider settings where a collective intelligence is formed by aggregating information contributed from many independent agents, such as product reviews, community sensing, or opinion polls. We propose a novel mechanism that elicits both private signals ...

2014

Data compression to define information content of hydrological time series

Marc Parlange, Steven Vincent Weijs, Nicolaas Cornelis van de Giesen

When inferring models from hydrological data or calibrating hydrological models, we are interested in the information content of those data to quantify how much can potentially be learned from them. In this work we take a perspective from (algorithmic) inf ...

Copernicus Gesellschaft Mbh2013