The Demographic Profile Most at Risk of being Disinformed

This paper explores the relationship between a person's demographic data, age (IV1), gender (IV2), ethnicity (IV3), and political ideology (IV4), and the risk of him/her falling prey to Mis/Disinformation attacks (DV). Participants ( n=161) were subjected to the Fake News and deepfake test (15-item). The main data analysis tool employed by this study is multiple linear regression. Important findings of the study include the revelation of the disparity in the performance of the subjects from the underrepresented groups against those who are not. This paper further confirms that an increase in age is a risk for being Disinformed. The predictive model further reveals the profile of a most likely Disinformation victim. The intended target audiences of this paper are policymakers, social scientists, and tech companies.