MULTI-Fake-DetectiVE at EVALITA 2023: Overview of the MULTImodal Fake News Detection and VErification Task

This paper introduces the MULTI-Fake-DetectiVE shared task for the EVALITA 2023 campaign. The task was aimed at exploring multimodality within the realm of fake news and intended to address the problem from two perspectives, represented by the two sub-tasks. In sub-task 1, we aimed to evaluate the effectiveness of multimodal fake news detection systems. In sub-task 2, we sought to gain insights into the interplay between text and images, specifically how they mutually influence the interpretation of content in the context of distinguishing between fake and real news. Both perspectives were framed as classification problems. The paper presents an overview of the task. In particular, we detail the key aspects of the task, including the creation of a new dataset for fake news detection in Italian, the evaluation methodology and criteria, the participant systems, and their results. In light of the obtained results, we argue that the problem is still open and propose some future directions.