Self-organization in social tagging systems

Abstract

Individuals often imitate each other to fall into the typical group, leading to a self-organized state of typical behaviors in a community. In this paper, we model self-organization in social tagging systems and illustrate the underlying interaction and dynamics. Specifically, we introduce a model in which individuals adjust their own tagging tendency to imitate the average tagging tendency. We found that when users are of low confidence, they tend to imitate others and lead to a self-organized state with active tagging. On the other hand, when users are of high confidence and are stubborn for changes, tagging becomes inactive. We observe a phase transition at a critical level of user confidence when the system changes from one regime to the other. The distributions of post length obtained from the model are compared to real data which show good agreements.

6 pages, 6 figures

References in corpus (8)

• Nonequilibrium phase transition in the coevolution of networks and opinions
• Collaborative Tagging and Semiotic Dynamics
• Random hypergraphs and their applications
• Personalized Recommendation via Integrated Diffusion on User-Item-Tag Tripartite Graphs
• Collective dynamics of social annotation
• Non-equilibrium phase transition in negotiation dynamics
• Fundamental statistical features and self-similar properties of tagged networks
• Empirical analysis on a keyword-based semantic system