posted on 2023-05-20, 12:03authored byLi, W, Quan BaiQuan Bai, Zhang, MJ, Nguyen, TD
Social influence modelling and maximization appear significant in various domains, such as e-business, marketing, and social computing. Most existing studies focus on how to maximize positive social impact to promote product adoptions based on static network snapshots. Such approaches can only increase influence in a social network in short-term, but cannot generate sustainable or long-term effects. In this research work, we study how to maintain long-term influence in a social network and propose an agent-based influence maintenance model, which can select influential nodes based on the current status in dynamic social networks in multiple times. Within the context of our investigation, the experimental results indicate that multiple-time seed selection is capable of achieving more constant impact than that of one-shot selection. We claim that influence maintenance is crucial for supporting, enhancing, and assisting long-term goals in business development. The proposed approach can automatically maintain long-lasting impact and achieve influence maintenance.
History
Publication title
IEEE Transactions on Knowledge and Data Engineering
Volume
31
Pagination
1884-1897
ISSN
1041-4347
Department/School
School of Information and Communication Technology
Publisher
Ieee Computer Soc
Place of publication
10662 Los Vaqueros Circle, Po Box 3014, Los Alamitos, USA, Ca, 90720-1314