Modeling interactions in social media networks using an asynchronous and synchronous opinion dynamics

Social media networks have become a powerful platform for shaping public opinion. In such networks, opinions change through complex processes. To better understand this process, we present a novel method to examine the specific dynamics of social media interactions and information spread. In this model, each person has both private and public opinions. Private opinions are continuously adjusted based on others’ public opinions and personal biases. In contrast, public opinions are updated only when expressed, shaped by the individual’s private opinion and a tendency to conform to widely accepted group views and social pressure. We analyze the model’s two-state updating mechanisms and provide conditions for opinion convergence. Our findings on the consensus dynamics are presented, along with implications for social interactions in social media networks. The proposed model is validated by comparing real social media Twitter data to the simulated results.