Uncovering User Interaction Dynamics in Online Social Networks


  • Zhi Yang Peking University
  • jilong xue Peking University
  • Christo Wilson Northeastern University
  • Ben Zhao University of California, Santa Barbara
  • Yafei Dai Peking University




Measurement studies of online social networks (OSNs)show that all social links are not equal, and the strength of each link is best characterized by the frequency of interactions between the linked users. To date, few studieshave been able to examine detailed interactiondata over time. In this paper, we first analyze the interaction dynamics in a large online social network. We find that users invite new friends to interact at a nearly constant rate, prefer to continue interacting with friends with whom they have a larger number of historical interactions,and most social links drop in interaction frequency over time. Then, we use our insights from the analysis to derive a generative model of social interactionsthat can capture fundamental processes underlinguser interactions.




How to Cite

Yang, Z., xue, jilong, Wilson, C., Zhao, B., & Dai, Y. (2021). Uncovering User Interaction Dynamics in Online Social Networks. Proceedings of the International AAAI Conference on Web and Social Media, 9(1), 698-701. https://doi.org/10.1609/icwsm.v9i1.14654