|Maximizing Time-discounted Influential Sustainability in Social Networks|
|Zeng, Shuai1,2; Ni, Xiaochun1,2; Li, Juanjuan1,2; Yuan, Yong1,2; Wang, Shuai1,3|
|会议名称||IEEE SMC Workshop on Social Computing and Social Intelligence|
|会议日期||Oct. 5-8, 2017|
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|
|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
|Zeng, Shuai,Ni, Xiaochun,Li, Juanjuan,et al. Maximizing Time-discounted Influential Sustainability in Social Networks[C],2017.|
|social marketing.pdf（194KB）||会议论文||开放获取||CC BY-NC-SA||浏览 下载|