282 citations · 995 across the 19 of their papers we have counts for
19 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…
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…
A Systematic Review of Generative AI for Teaching and Learning Practice
Bayode Ogunleye, Kudirat Ibilola Zakariyyah, Oluwaseun Ajao +2
The use of generative artificial intelligence (GenAI) in academia is a subjective and hotly debated topic. Currently, there are no agreed guidelines towards the usage of GenAI syst…
Higher education assessment practice in the era of generative AI tools
Bayode Ogunleye, Kudirat Ibilola Zakariyyah, Oluwaseun Ajao +2
The higher education (HE) sector benefits every nation's economy and society at large. However, their contributions are challenged by advanced technologies like generative artifici…
Analysing the Influence of Macroeconomic Factors on Credit Risk in the UK Banking Sector
Hemlata Sharma, Aparna Andhalkar, Oluwaseun Ajao +1
Macroeconomic factors have a critical impact on banking credit risk, which cannot be directly controlled by banks, and therefore, there is a need for an early credit risk warning s…
Exploring Content-Based and Meta-Data Analysis for Detecting Fake News Infodemic: A case study on COVID-19
Oluwaseun Ajao, Ashish Garg, Marjory Da Costa-Abreu
The coronavirus pandemic (COVID-19) is probably the most disruptive global health disaster in recent history. It negatively impacted the whole world and virtually brought the globa…
Content-Aware Tweet Location Inference using Quadtree Spatial Partitioning and Jaccard-Cosine Word Embedding
Oluwaseun Ajao, Deepayan Bhowmik, Shahrzad Zargari
Inferring locations from user texts on social media platforms is a non-trivial and challenging problem relating to public safety. We propose a novel non-uniform grid-based approach…
Fake News Identification on Twitter with Hybrid CNN and RNN Models
Oluwaseun Ajao, Deepayan Bhowmik, Shahrzad Zargari
The problem associated with the propagation of fake news continues to grow at an alarming scale. This trend has generated much interest from politics to academia and industry alike…
Tweet for Behavior Change: Using Social Media for the Dissemination of Public Health Messages
Aisling Gough, Ruth F Hunter, Oluwaseun Ajao +8
Background: Social media public health campaigns have the advantage of tailored messaging at low cost and large reach, but little is known about what would determine their feasibil…
Location Inference from Tweets using Grid-based Classification
Oluwaseun Ajao, Deepak P, Jun Hong
The impact of social media and its growing association with the sharing of ideas and propagation of messages remains vital in everyday communication. Twitter is one effective platf…
Feasibility Study of Social Media for Public Health Behaviour Changes
Oluwaseun Ajao, Anna Jurek, Aisling Gough +5
Social networking sites such as Twitter and Facebook have been shown to function as effective social sensors that can "feel the pulse" of a community. The aim of the current study…
A survey of location inference techniques on Twitter
Oluwaseun Ajao, Jun Hong, Weiru Liu
The increasing popularity of the social networking service, Twitter, has made it more involved in day-to-day communications, strengthening social relationships and information diss…