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

Descrizione del progetto

Il calcolo distribuito per eliminare le notizie false

La lotta contro le notizie false è reale: le persone in tutto il mondo sono esposte a una disinformazione su larga scala, che comprende informazioni fuorvianti o false. La Commissione europea si è posta la priorità di lottare contro la diffusione e le ripercussioni della disinformazione online (definita come «informazioni verificabili false o fuorvianti create, presentate e diffuse per guadagno economico o per ingannare intenzionalmente il pubblico»). La disinformazione può provocare danni pubblici, minacciare le democrazie e mettere a rischio la salute, la sicurezza e l’ambiente dei cittadini europei. Il progetto FARE, finanziato dall’UE, svilupperà una strategia basata sul calcolo distribuito, nonché linee guida per la gestione etica dei megadati correlati agli esseri umani. Risponderà alle seguenti domande: qual è il ruolo dei pregiudizi cognitivi? In che modo l’architettura di rete condiziona la forza delle notizie false?

Obiettivo

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.

Meccanismo di finanziamento

ERC-STG - Starting Grant

Istituzione ospitante

LABORATORIO DE INSTRUMENTACAO E FISICA EXPERIMENTAL DE PARTICULAS LIP
Contribution nette de l'UE
€ 1 499 844,00
Indirizzo
RUA LARGA 4 UNIVERSIDADE DE COIMBRA
3004 516 Coimbra
Portogallo

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Regione
Continente Centro (PT) Região de Coimbra
Tipo di attività
Research Organisations
Collegamenti
Costo totale
€ 1 499 844,00

Beneficiari (1)