282 citations · 562 across the 12 of their papers we have counts for
11 papers
A Multi-Branch Feature Fusion Approach for Health Misinformation Detection and Propagation
Mkululi Sikosana, Sean Maudsley-Barton, Oluwaseun Ajao
This paper presents a multi-branch fusion framework for detecting and characterising the propagation of health misinformation in online social networks (OSNs). Grounded in the Elab…
BERTopic-Virality Prioritisation: A Scalable Framework for Thematic and Comparative Analysis of COVID-19 and Monkeypox Misinformation on Twitter
Mkululi Sikosana, Sean Maudsley-Barton, Oluwaseun Ajao
Health misinformation circulating during pandemics can gain traction rapidly, creating harmful narratives that compete with public health guidance. Most topic-modelling pipelines t…
Integrating Persuasion Theory into the Epidemiological Modelling of Health Misinformation Spread on Social Media
Mkululi Sikosana, Sean Maudsley-Barton, Oluwaseun Ajao
This study presents a hybrid epidemiological and behavioural framework to simulate the spread of health misinformation on social media. We extend the classical Susceptible--Infecte…
Safeguarding Efficacy in Large Language Models: Evaluating Resistance to Human-Written and Algorithmic Adversarial Prompts
Tiarnaigh Downey-Webb, Olamide Jogunola, Oluwaseun Ajao
This paper presents a systematic security assessment of four prominent Large Language Models (LLMs) against diverse adversarial attack vectors. We evaluate Phi-2, Llama-2-7B-Chat,…
Linguistic Patterns in Pandemic-Related Content: A Comparative Analysis of COVID-19, Constraint, and Monkeypox Datasets
Mkululi Sikosana, Sean Maudsley-Barton, Oluwaseun Ajao
This study conducts a computational linguistic analysis of pandemic-related online discourse to examine how language distinguishes health misinformation from factual communication.…
Differential Robustness in Transformer Language Models: Empirical Evaluation Under Adversarial Text Attacks
Taniya Gidatkar, Oluwaseun Ajao, Matthew Shardlow
This study evaluates the resilience of large language models (LLMs) against adversarial attacks, specifically focusing on Flan-T5, BERT, and RoBERTa-Base. Using systematically desi…