Multimodal Propaganda Processing
Vincent Ng, Shengjie Li

TL;DR
This paper introduces the task of multimodal propaganda processing, aiming to automatically analyze propaganda content combining multiple data modalities, which is a significant step towards AI understanding of biased information.
Contribution
It defines the new task of multimodal propaganda analysis and discusses the technical challenges and future steps to enable AI systems to understand propaganda content.
Findings
Highlights the importance of multimodal analysis for propaganda detection
Identifies key technical challenges in processing biased content
Outlines future research directions for AI understanding of propaganda
Abstract
Propaganda campaigns have long been used to influence public opinion via disseminating biased and/or misleading information. Despite the increasing prevalence of propaganda content on the Internet, few attempts have been made by AI researchers to analyze such content. We introduce the task of multimodal propaganda processing, where the goal is to automatically analyze propaganda content. We believe that this task presents a long-term challenge to AI researchers and that successful processing of propaganda could bring machine understanding one important step closer to human understanding. We discuss the technical challenges associated with this task and outline the steps that need to be taken to address it.
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Taxonomy
TopicsMisinformation and Its Impacts · Topic Modeling · Hate Speech and Cyberbullying Detection
