Decoding user behaviour: identifying user's prone to misinformation sharing on social media during disasters

The rapid dissemination of misinformation on social media has become a significant societal issue. This study investigates the factors influencing users' beliefs and behaviours of sharing misinformation on social media. A mixed-method approach has been employed in which the trusts and beliefs associated with misinformation sharing are analysed through qualitative literature reviews, while user behaviour on information sharing is analysed using an unsupervised machine learning approach. By triangulating the findings from both approaches, this study offers vital insights into identifying the fake news spreader behaviour from a user recipient perspective. The research also proposes a conceptual model to empower recipient users to mitigate the spread of fake news. The key findings and conceptual model can inform the development of policies and strategies by users, government, and platform providers to combat the spread of fake news.