Fake news sharing among Weibo users in China - Luo, Dong; Nur Haniz Mohd Nor,; Kai, Ge Bai; Siti Syuhada Abdul Rais,; Azian Muhamad Adzmi, (Penerbit Universiti Kebangsaan Malaysia, 2023)
In an era where social media's impact on public discourse is increasingly pronounced, this study probes into the spread of fake news among Weibo users in China, a significant issue given the platform's massive user base and China's unique media environment. Adopting a quantitative research approach, the study primarily investigates how situational motivation and information-seeking behaviours influence the sharing of fake news. Utilising regression analysis, a method pivotal for understanding the relationship between various independent variables and the sharing of misinformation, the research sheds light on the nuanced interplay of factors that drive users to disseminate false information. Key findings reveal that situational factors, such as the need for social recognition or the urge to disseminate urgent news, considerably elevate the likelihood of sharing fake news. Additionally, the study uncovers the complex nature of information-seeking behaviour: while it generally leads to better-informed decisions, it can sometimes result in the sharing of unverified news under certain circumstances. These outcomes are crucial for understanding the behavioural patterns behind fake news sharing on social media. They offer valuable insights for policymakers, social media platforms, and educators in formulating effective countermeasures against misinformation, aiming to foster a more discerning and informed online community. This study, therefore, contributes significantly to the existing body of knowledge on digital media, misinformation, and public opinion, highlighting the critical need for strategies to combat the spread of fake news in the digital age.