An improved PageRank algorithm for Social Network User’s Influence research
- https://doi.org/10.2991/icmii-15.2015.93How to use a DOI?
- Social network; PageRank algorithm; User’s influence; Forwarding rate; Activity degree
In social networks, Micro Blog has become the most widely used social networking platform. Mining valuable customers is particularly important in the large-scale micro-blog user group, and the influence of the user become the main measure to estimate the user's value. Based on the similarity of micro-blog user groups and Internet node characteristics in structure, this paper proposed an improved PageRank algorithm by user forwarding rate and activity degree estimate the user’s influence. Experiment results show that the improved algorithm has good convergence and the influence of the micro blog users can estimate effectively and objectively.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Peng Wang AU - Xue Bo AU - Huamin Yang AU - Shuangzi Sun AU - Songjiang Li PY - 2015/10 DA - 2015/10 TI - An improved PageRank algorithm for Social Network User’s Influence research BT - Proceedings of the 3rd International Conference on Mechatronics and Industrial Informatics PB - Atlantis Press SP - 542 EP - 547 SN - 2352-538X UR - https://doi.org/10.2991/icmii-15.2015.93 DO - https://doi.org/10.2991/icmii-15.2015.93 ID - Wang2015/10 ER -