Including Images into Message Veracity Assessment in Social Media
Abderrazek Azri (ERIC), C\'ecile Favre (ERIC), Nouria Harbi (ERIC),, J\'er\^ome Darmont (ERIC)

TL;DR
This paper proposes a framework that enhances social media message veracity assessment by incorporating analysis of both textual and visual (image) content, addressing a gap in existing research.
Contribution
It introduces a novel approach that combines textual and visual content analysis for more accurate social media message veracity evaluation.
Findings
Framework explores two new methods for veracity assessment.
Integrates visual content analysis into existing textual analysis.
Addresses the gap of visual content utilization in veracity studies.
Abstract
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…
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Taxonomy
TopicsMisinformation and Its Impacts · Complex Network Analysis Techniques · Opinion Dynamics and Social Influence
MethodsDiffusion
