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8 articles for “Identifying misinformation”
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Scalable System for Identifying and Flagging Misinformation Using AI/ML and DL
Abstract: The fast spread of realistic fake media means we need to make a system to identify false information that can work with a lot of data. This system is called the Scalable Misinformation Identification System or SMIS for short. SMIS helps keep our society and democracy safe from the threats of news on the internet. The old ways of checking for news and simple machine learning models are not good …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 2, 2025 · pp. 33–40 Read article
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AI- based Prediction of Misinformation Virality Before Wide Dissemination using Attention-based Multi-modal
Abstract: Misinformation on social media has emerged as a critical global challenge, impacting public health, democratic institutions, and societal trust. While existing research has largely concentrated on detecting misinformation after it begins circulating, predicting its virality before wide dissemination remains an underexplored area, limited work addresses predicting its virality before wide dissemination. This paper presents a conceptual framework using attention-based multi-modal deep learning models to estimate the virality of misinformation posts …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 3, 2025 Read article
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Misinformation Detection and Analysis of Social Media Platforms Using Machine Learning and Deep Learning
Abstract: Social media platforms have become deeply embedded in everyday life, reshaping how people produce, distribute, and engage with information. Although these platforms facilitate quick communication, they have also developed into important avenues for the spread of false information and fake news. The increasing volume of online content makes manual verification impractical, creating a need for reliable automated detection systems. The effectiveness of deep learning and machine learning models in spotting …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 2, 2026 · pp. 22–34 Read article
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An Intelligent AI–ML Framework for Deepfake Generation and Detection
Abstract: Recent developments in Artificial Intelligence (AI) and Machine Learning (ML) have led to the rise of deepfake technology, making it one of the most impactful innovations in the digital world. Deepfakes are synthetic forms of digital media generated using deep learning algorithms capable of realistically manipulating facial expressions, voice patterns, images, and video content. Although these technologies provide innovative applications in entertainment, virtual reality, healthcare, and education, their misuse has …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 2, 2025 · pp. 25–32 Read article
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Instagram Therapists vs. Qualified Mental Health Professionals: How Young Adults Perceive and Navigate Mental Health Advice Online
Abstract: The growing presence of “Instagram Therapists” - individuals who share mental health advice on Instagram without formal qualifications - has raised important questions about the credibility of online mental health information. In contrast, are qualified mental health professionals and licensed practitioners. Existing literature shows a surge in young adults turning to social media for mental health guidance. However, limited research delves into how they perceive and differentiate between advice from …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 2, 2025 · pp. 26–37 Read article
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Secure Forge: Deepfake Image Detection Using Vision Transformers
Abstract: Deepfake technologies have become a major risk to the credibility and trustworthiness of digital visual information. Using powerful generative models like GANs and autoencoders, deepfakes can generate highly realistic fake videos and images, resulting in misinformation, identity theft, and public loss of trust in digital media. Classic Convolutional Neural Networks (CNNs) while being highly effective in initial-stage, deepfake detection tend to be limited by their local receptive fields and dependency …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 32–45 Read article
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Impact of Vaccine Awareness Campaigns on Pharmacovigilance Reporting and Public Safety Monitoring
Abstract: Vaccination programs have significantly contributed to the reduction of infectious diseases worldwide; however, their success is closely tied to public confidence and robust safety monitoring systems. Pharmacovigilance plays a critical role in identifying, assessing, and preventing adverse events following immunization (AEFI). In recent years, vaccine awareness campaigns have emerged as a pivotal strategy to improve public knowledge, reduce vaccine hesitancy, and enhance reporting of adverse drug reactions (ADRs). This review …
Published in International Journal of Vaccines · Vol. 3, Issue 2, 2026 · pp. 1–14 Read article
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The Awareness–Behaviour Paradox: Media Literacy and Social Media Risk Behaviour Among Nigerian Undergraduates
Abstract: Background: The proliferation of internet-capable devices and social media platforms has created an intricate web of risks for Nigerian undergraduates, including cyberbullying, addiction, misinformation, and exposure to indecent content. While media literacy has been widely proposed in Western scholarship as a sustainable intervention for responsible online behaviour, its protective mechanisms remain insufficiently understood in non-Western contexts, particularly with respect to the psychological pathways through which literacy operates.Objectives: This study examined …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 121–126 Read article