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FARE

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FAKE NEWS AND REAL PEOPLE USING BIG DATA TO UNDERSTAND HUMAN BEHAVIOUR

Recent events, from the anti-vaccination movement, to Brexit and even to mob killings, have raised serious concerns about the influence of the so-called fake news (FN). False information is not new in human history, but the recent... ver más

30/09/2025

LIP

1M€

Presupuesto del proyecto: 1M€

Líder del proyecto

LABORATORIO DE INSTRUMENTACAO E FISICA EXPERI... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

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Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2020-09-24

ERC-2019-STG: ERC Starting Grant

I+D

Cerrada hace 6 años

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No hay información privada compartida para este proyecto. Habla con el coordinador.

2 Participantes

LIP

1.50M€ | Lider

HYBTRONICS MICROSYSTEMS

1.04M€ | Participante

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Duración del proyecto: 60 meses Fecha Inicio: 2020-09-24
Fecha Fin: 2025-09-30

Líder del proyecto

LABORATORIO DE INSTRUMENTACAO E FISICA EXPERI... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 1M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Recent events, from the anti-vaccination movement, to Brexit and even to mob killings, have raised serious concerns about the influence of the so-called fake news (FN). False information is not new in human history, but the recent surge in online activity, coupled with poor digital literacy, consumer profiling, and large profits from ad revenues, created a perfect storm for the FN epidemic, with still unimaginable consequences. This challenge is interdisciplinary and requires academic research to guide current calls for action issued by academics, governmental and non-governmental agencies, and the social network platforms themselves. FARE will enrich current efforts, which mostly confront FN spreading from an applied perspective, by offering a theoretical framework that allows to make testable predictions. FARE argues that sharing of FN is a deviation from pure rationality and brings together 1) state of the art knowledge in behavioural psychology, to assess the role that cognitive biases play in susceptibility to FN, and 2) current models in network science and epidemiology, to test whether FN spread more like simple or complex contagions. Finally, fully recognizing that these novel big-data approaches carry great risks, FARE will develop a new strategy, mostly based on distributed computing, and guidelines to the ethical handling of human-related big-data. Together, FARE will offer a comprehensive model to ask questions such as: 1) What role(s) cognitive biases play in FN spreading? 2) How does network architecture affect FNs spread? 3) How do biases and position on networks build on each other to impact propagation? 4) What monitoring and mitigation interventions are likely to be more efficient? Moreover, the study of FN from such a conceptual perspective has the potential to profoundly increase our knowledge on human behaviour and information spread, beyond specific problems, with implications for communication (science, political), economics, and psychology.

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