Models for the Diffusion of Beliefs in Social Networks: An Overview

Christophe Chamley (), Anna Scaglione and Lin Li
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Christophe Chamley: PSE - Paris-Jourdan Sciences Economiques - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - INRA - Institut National de la Recherche Agronomique - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, Department of Economics - BU - Boston University [Boston]
Anna Scaglione: Department of Economics - BU - Boston University [Boston]
Lin Li: Department of Economics - BU - Boston University [Boston]

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Abstract: Signal processing is very much tied to extracting information and making inferences from physical phenomena. The traditional modalities to which our field is given credit for advancing are speech, images, video, communication signals, remote sensing, and a number of biomedical sensors that digital and array processing methods enable. More recently, brain?machine interfaces (BMIs) have also become a research focus of signal processing researchers. We continue to fill the gap between human signals and computers, leading to today?s highly computerized social landscape.

Date: 2013-05
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Published in IEEE Signal Processing Magazine, 2013, 30 (3), pp.16-29. ⟨10.1109/MSP.2012.2234508⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-00812894

DOI: 10.1109/MSP.2012.2234508

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