TY  - JOUR
AU  - Xie, Jianye
AU  - Wang, Xudong
AU  - Liu, Yuwen
AU  - Gong, Wenwen
AU  - Yan, Chao
AU  - Rafique, Wajid
AU  - Khan, Maqbool
AU  - Khan, Arif Ali
PY  - 2025
TI  - Social Media-Driven User Community Finding with Privacy Protection
JO  - Tsinghua Science and Technology
SN  - 1007-0214
SP  - 1782
EP  - 1792
VL  - 30
IS  - 4
AB  - 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.
UR  - https://doi.org/10.26599/TST.2024.9010065
DO  - 10.26599/TST.2024.9010065