Toward the Prevention of Privacy Threats: How Can We Persuade Our Social Network Platform Users?

Complex decision-making problems, such as the privacy policy selection, when sharing content in online social network (OSN) platforms can significantly benefit from artificial intelligence systems. With the use of computational argumentation, it is possible to persuade human users to modify their initial decisions to avoid potential privacy threats and violations. In this paper, we present a study performed with the participation of 186 teenage users aimed at analyzing their behaviors when we try to persuade them to modify the post/publication of sensitive content on OSN platforms with different arguments. The results of the study revealed that the personality traits and the social interaction data (e.g., number of comment posts, friends, and likes) of our participants were significantly correlated with the persuasive power of the arguments. Therefore, these sets of features can be used to model OSN users and estimate the persuasive power of different arguments when used in human-computer interactions. The findings presented in this paper are helpful for personalizing decision support systems aimed at educating and preventing privacy violations on OSN platforms using arguments.