2023/11/06 by Yunze Xiao, Xiao, Yunze, Firoj Alam +1
Computer Science · Social Sciences · #68T50 #Anonymity #Arabic #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Computer science #Computer security #Context (archaeology) #Disinformation #Exploit #F.2.2 #FOS: Computer and information sciences #Hate Speech and Cyberbullying Detection #History #I.2.7 #Internet privacy #Linguistics #Misinformation and Its Impacts #Political science #Social and Information Networks (cs.SI) #Social media #Spam and Phishing Detection #World Wide Web
paper · pdf · doi:10.48550/arxiv.2311.03184
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2023/11/06 · openalex created_date 2023/11/08 · openalex updated_date 2026/07/28
The spread of disinformation and propagandistic content poses a threat to societal harmony, undermining informed decision-making and trust in reliable sources. Online platforms often serve as breeding grounds for such content, and malicious actors exploit the vulnerabilities of audiences to shape public opinion. Although there have been research efforts aimed at the automatic identification of disinformation and propaganda in social media content, there remain challenges in terms of performance. The ArAIEval shared task aims to further research on these particular issues within the context of the Arabic language. In this paper, we discuss our participation in these shared tasks. We competed in subtasks 1A and 2A, where our submitted system secured positions 9th and 10th, respectively. Our experiments consist of fine-tuning transformer models and using zero- and few-shot learning with GPT-4.