The impact of personality in recognizing disinformation

The purpose of this paper is to investigate and quantify the effects of personality traits, as defined by the five-factor model (FFM) on an individual’s ability to detect fake news. The findings of this study are increasingly important because of the proliferation of social media news stories and the exposure of organizational stakeholders and business decision makers to a tremendous amount of information, including information that is not correct (a.k.a. disinformation).

The data were collected utilizing the snowball sampling methodology. Students in an Management Information Systems course completed the survey. Since a diverse sample was sought, survey participants were instructed to recruit another individual from a different generation. The survey questions of the FFM identify particular personality traits in respondents. Survey respondents were given a collection of nine news stories, five of which were false and four that were true. The number of correctly identified stories was recorded, and the effect of personality traits on the ability of survey respondents to identify fake news was calculated using eta-squared and the effect size index.

Each of the five factors in the FFM demonstrated an effect on an individual’s ability to detect disinformation. In fact, every single variable studied had at least a small effect size index, with one exception: gender, which had basically no effect. Therefore, each variable studied (with the exception of gender) explained a portion of the variability in the number of correctly identified false news stories. Specifically, this quantitative research demonstrates that individuals with the following personality traits are better able to identify disinformation: closed to experience or cautious, introverted, disagreeable or unsympathetic, unconscientious or undirected and emotionally stable.

There is scant research on an individual’s ability to detect false news stories, although some research has been conducted on the ability to detect phishing (a type of social engineering attack to obtain funds or personal information from the person being deceived). The results of this study enable corporations to determine which of their customers, investors and other stakeholders are most likely to be deceived by disinformation. With this information, they can better prepare for and combat the impacts of misinformation on their organization, and thereby avoid the negative financial impacts that result.