Over the recent decades, we have witnessed the flourish of online social networks. Due to the proliferation of these networks, there have been unprecedented changes in the way individuals communicate and do activities. Online social networks may play an effective role in how individuals form opinions and make decisions since these networks have provided fast and wide diffusion of information through propagation among users. Diffusion in online social networks may positively affect societies by warning during disasters, increasing civic engagement, mobilizing liberation campaigns and boosting marketing. However, diffusion in such networks gives rise to some adverse effects. First, misinformation can be diffused fast and widely too; misinformation propagation has become a significant threat in online social networks. Second, as these networks tend to connect primarily like-minded individuals, they often create so-called bubbles where users are presented with information that predominantly matches their existing opinions. This phenomenon reinforces users' existing opinions and polarizes them into non-interacting groups. Thus, diffusion may have a double-edge effect in social networks. Not all users play the same role in diffusion in online social networks. So-called influential users play an important role, due to their characteristics and friends in the networks. Given the effects of diffusion in online social networks on societies, it is crucial to measure the influence of users and intervene in the networks to adjust their influence. These effects motivate the current thesis to analyse the pattern of such diffusion and explore the role of users and their interactions in the pattern. This analysis is important to help deal with the double-edged effects of diffusion in online social networks. More specifically, in this thesis, we explore the pattern of diffusion in online social networks to address how to measure and adjust the influence of users to deal with the positive and negative effects of diffusion in online social networks. To measure the influence of users, we assess factors that may affect the pattern of diffusion in online social networks and discuss the role of two affecting factors (the activity level of users and misinformation diffusion) that have not been addressed in the literature. Different models are developed to capture the effects of these factors on the pattern of diffusion. Then, we suggest different methods to measure the influence of users and identify influential users. To adjust the influence of users, first, we discuss how the inequality in the influence of users and connectivity to like-minded individuals may negatively affect the diffusion process in a network. Then, we suggest different methods to adjust the influence of users and mitigate the negative effects. The thesis concludes with a discussion of research findings and directions for future studies.
- Social Network Analysis
- User Influence
- Diffusion Process
User Influence in Online Social Networks: Measurement and Adjustment
Zareie, A. (Author). 31 Dec 2023
Student thesis: Phd