A predictive model for estimating citizens’ beliefs regarding the risk perception of dissemination and dispersal of fake content

Written by Iuliana Mihaela Lazar, Ana Catalina Paun on . Posted in Volume XXIV, Nr 3


Iuliana Mihaela Lazar1,2*, Ana Catalina Paun2

1 University of Bucharest, Teacher Training Department, Bucharest, Romania
2 InfoCons Association, Bucharest, Romania


The present study explored if and how the different trust levels in various sources of news were correlated with the risk perception of dissemination and dispersal of fake content. Several results of the Flash Eurobarometer survey conducted by the TNS Political and Social network in 2018 about fake news and disinformation online was used as research information. Average data of the 28 European Union countries corresponding to trust levels (e.g., totally trust, tend to trust, tend not to trust, do not trust at all and don't know) and perceived risks related to false news were exploited to build an adequate multiple linear regression (MLR) model to predict citizens' beliefs regarding risk perception for their country. The relationship of socio-demographic variables (i.e., gender and age group) to the model was also examined. The results indicated that the predictive model has good psychometric properties but cannot be generalized for all population categories. The MLR model for forecasting of the EU citizens’ beliefs concerning the existence of risk perceptions of false news expansion in society fitted the data associated with various trust levels well in terms of Adjusted R2 =.405, p =.003. However, the beliefs of those who have total or partial confidence in various news cannot be explained by the model. Moreover, the results highlighted the presence of a vulnerable group composed by young people under 24-years of age with uncommon beliefs regarding risk perception of dissemination and dispersal of fake content. Thus, detailed studies are required in this direction for the future.

Keywords: disinformation online, European Union, fake news, human beliefs, perceived risks, predictive model



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