Maximizing Time-discounted Influential Sustainability in Social Networks
Zeng, Shuai1,2; Ni, Xiaochun1,2; Li, Juanjuan1,2; Yuan, Yong1,2; Wang, Shuai1,3
2017
会议名称IEEE SMC Workshop on Social Computing and Social Intelligence
会议日期Oct. 5-8, 2017
会议地点Banff, Canada
摘要
n social marketing practice, it is usually important to anticipate the long-term impact of the target application to maintain a long-lasting marketing effect, whereas a new product or technology should spread as quickly as possible to establish a competitive advantage.
To find a balance between them, we tackle this challenge by modelling the problem as an issue of time-discounted influential sustainability. Given a threshold µ, the goal of the problem is finding a small subset of nodes as seeds and deciding the optimal timing to activate each seed that could maximize the time-discounted number of iterations, each of which actives more than µ nodes.
 We prove that solving the problem is NP-hard and the objective function is non-negative, non-monotonic, and non-submodular. Therefore we propose a greedy approach to approximately solve this problem. Our experimental results demonstrate that our solution outperforms two baseline algorithms. In order to provide meaningful advices for advertisers on selecting proper initial seed users, we further analyze and compare the performance of four seeding strategies on three typical types of social networks. 
关键词Social Marketing Influence Sustainability Information Diffusion Seeding Strategy
收录类别EI
语种英语
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/19718
专题多模态人工智能系统全国重点实验室_平行智能技术与系统团队
通讯作者Yuan, Yong
作者单位1.The State Key Lab of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences
2.Qingdao Academy of Intelligent Industries
3.University of Chinese Academy of Sciences
第一作者单位中国科学院自动化研究所
通讯作者单位中国科学院自动化研究所
推荐引用方式
GB/T 7714
Zeng, Shuai,Ni, Xiaochun,Li, Juanjuan,et al. Maximizing Time-discounted Influential Sustainability in Social Networks[C],2017.
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