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Automated Influence Maintenance in Social Networks: An Agent-based Approach
Citation
Li, W and Bai, Q and Zhang, MJ and Nguyen, TD, Automated Influence Maintenance in Social Networks: An Agent-based Approach, IEEE Transactions on Knowledge and Data Engineering, 31 pp. 1884-1897. ISSN 1041-4347 (2019) [Refereed Article]
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DOI: doi:10.1109/TKDE.2018.2867774
Abstract
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.
Item Details
| Item Type: | Refereed Article |
|---|---|
| Keywords: | influence maintenance, influence diffusion, long-lasting influence, agent-based modelling, multi-agent systems, social network analysis |
| Research Division: | Information and Computing Sciences |
| Research Group: | Artificial intelligence |
| Research Field: | Intelligent robotics |
| Objective Division: | Information and Communication Services |
| Objective Group: | Information systems, technologies and services |
| Objective Field: | Application software packages |
| UTAS Author: | Bai, Q (Dr Quan Bai) |
| ID Code: | 138120 |
| Year Published: | 2019 |
| Web of Science® Times Cited: | 11 |
| Deposited By: | Information and Communication Technology |
| Deposited On: | 2020-03-25 |
| Last Modified: | 2020-08-21 |
| Downloads: | 18 View Download Statistics |
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