On Effective Ways to Warn People Against Misleading Contents

Nowadays, means and services devoted to spreading news, information and opinions on the Internet are increasingly targeted by attacks aimed at inoculating malicious content with the aim of creating harmful effects on users, such as altering their perception of reality as well as influencing their opinions and choices. Plenty of promising solutions have been proposed to detect and classify such contents, according to their nature and scopes. Minor emphasis has been posed on choosing, for specific application contexts, the most effective way to warn users about dangerous contents. In this paper we first categorize different types of misleading information, identifying for of them peculiar aspects. Then, we report different methodologies that have been proposed to raise users’ attention against potentially malicious contents. We argue that different alerting tools provide reasonable protection in specific contexts while no general solution is still available for guaranteeing users’ security.