7 citations · 10 across the 7 of their papers we have counts for
8 papers
Does Neural Complexity Improve Health Misinformation Detection? A Leakage-Controlled Cross-Corpus Benchmark
Mkululi SIKOSANA
Increasing architectural complexity is often assumed to improve health misinformation detection, yet reported gains are difficult to interpret when studies use different corpora, p…
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…
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.…
Advanced Health Misinformation Detection Through Hybrid CNN-LSTM Models Informed by the Elaboration Likelihood Model (ELM)
Mkululi Sikosana, Sean Maudsley-Barton, Oluwaseun Ajao
Health misinformation during the COVID-19 pandemic has significantly challenged public health efforts globally. This study applies the Elaboration Likelihood Model (ELM) to enhance…
Analysing Health Misinformation with Advanced Centrality Metrics in Online Social Networks
Mkululi Sikosana, Sean Maudsley-Barton, Oluwaseun Ajao
The rapid spread of health misinformation on online social networks (OSNs) during global crises such as the COVID-19 pandemic poses challenges to public health, social stability, a…
A Comparative Study of Hybrid Models in Health Misinformation Text Classification
Mkululi Sikosana, Oluwaseun Ajao, Sean Maudsley-Barton
This study evaluates the effectiveness of machine learning (ML) and deep learning (DL) models in detecting COVID-19-related misinformation on online social networks (OSNs), aiming…