Including Images into Message Veracity Assessment in Social Media
This work addresses the challenge of misinformation in social media for users and platforms, but it is incremental as it builds on existing text-based methods by adding image analysis.
The paper tackles the problem of rumor spread in social media by proposing a framework that assesses message veracity through both textual and visual content analysis, addressing a gap where previous works focused only on text.
The extensive use of social media in the diffusion of information has also laid a fertile ground for the spread of rumors, which could significantly affect the credibility of social media. An ever-increasing number of users post news including, in addition to text, multimedia data such as images and videos. Yet, such multimedia content is easily editable due to the broad availability of simple and effective image and video processing tools. The problem of assessing the veracity of social network posts has attracted a lot of attention from researchers in recent years. However, almost all previous works have focused on analyzing textual contents to determine veracity, while visual contents, and more particularly images, remains ignored or little exploited in the literature. In this position paper, we propose a framework that explores two novel ways to assess the veracity of messages published on social networks by analyzing the credibility of both their textual and visual contents.