Jianye Xie;Xudong Wang;Yuwen Liu;Wenwen Gong;Chao Yan;Wajid Rafique;Maqbool Khan;Arif Ali Khan
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引用次数: 0
Abstract
In the digital era, social media platforms play a crucial role in forming user communities, yet the challenge of protecting user privacy remains paramount. This paper proposes a novel framework for identifying and analyzing user communities within social media networks, emphasizing privacy protection. In detail, we implement a social media-driven user community finding approach with hashing named MCF to ensure that the extracted information cannot be traced back to specific users, thereby maintaining confidentiality. Finally, we design a set of experiments to verify the effectiveness and efficiency of our proposed MCF approach by comparing it with other existing approaches, demonstrating its effectiveness in community detection while upholding stringent privacy standards. This research contributes to the growing field of social network analysis by providing a balanced solution that respects user privacy while uncovering valuable insights into community dynamics on social media platforms.
期刊介绍:
Tsinghua Science and Technology (Tsinghua Sci Technol) started publication in 1996. It is an international academic journal sponsored by Tsinghua University and is published bimonthly. This journal aims at presenting the up-to-date scientific achievements in computer science, electronic engineering, and other IT fields. Contributions all over the world are welcome.