Second Space: A Generative Model for the Blogosphere

Authors

  • Amit Karandikar University of Maryland, Baltimore County
  • Akshay Java, University of Maryland, Baltimore County
  • Anupam Joshi University of Maryland, Baltimore County
  • Tim Finin University of Maryland, Baltimore County
  • Yaacov Yesha University of Maryland, Baltimore County
  • Yelena Yesha University of Maryland, Baltimore County

Abstract

Analysing complex natural phenomena often requires synthesized data that matches observed characteristics. Graph models are widely used in analyzing the Web in general, but are less suitable for modeling the Blogosphere. While blog networks resemble many properties of Web graphs, the dynamic nature of the Blogosphere, its unique structure and the evolution of the link structure due to blog readership and social interactions are not captured by the existing models. We describe an agent-based simulation model to construct blog graphs that exhibit properties similar to the real world blog networks in their degree distributions, degree correlation, clustering coefficient and reciprocity. The model can help researchers analyze the Blogosphere and facilitates the development and testing of new algorithms.

Downloads

Published

2021-09-25

How to Cite

Karandikar, A., Java, A., Joshi, A., Finin, T., Yesha, Y., & Yesha, Y. (2021). Second Space: A Generative Model for the Blogosphere. Proceedings of the International AAAI Conference on Web and Social Media, 2(1), 198-199. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/18649