Opinion spreading and evolution in complex social networks: a simulation study

• Main Author: Wu, Yujie
• Other Authors: Xiao Gaoxi
• Format: Thesis-Master by Coursework
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Engineering
• Online Access: https://hdl.handle.net/10356/174295
• Institution: Nanyang Technological University

In an era marked by the growing impact of social media and the complexity of public opinion, research into social opinion evolution has become increasingly important. This dissertation provides a thorough examination of this field, proposing a new model that builds on existing classical frameworks. This model shows potential for revealing important insights into the development of public opinion dynamics within social networks, especially in the complexities of the current digital age. The study focuses on an innovative modification to traditional models, introducing the concept of interaction capacity. This new addition emphasizes the intuitive idea that individuals naturally aim for improved social adaptability. This modification emphasises the influence of active social engagement and the strategic adjustment of individual opinions within collective opinion dynamics, departing from conventional models that predominantly focus on opinion homogeneity. Experimental outcomes conducted across Erdős-Rényi and scale-free networks reveal the intricate influence of the pursuit of social influence and conformity on opinion dynamics. Modifying social interaction rules has a significant impact on the dynamic equilibrium of opinions and the phenomenon of social opinion polarization. These models offer profound insights into the complex dynamics of real-world opinion formation from a social psychology standpoint, providing a critical theoretical foundation for understanding and mitigating social polarization. In addition, this dissertation sheds light on how digital media platforms can amplify social influence and individual conformist tendencies. The innovative model and consequential findings of this dissertation promise to enrich our comprehension of the intricate interplay between individual opinions and collective social behavior in the digital information age. They offer invaluable perspectives for steering public discourse and grasping the subtleties of social opinion dynamics with greater acuity.