Title
Influential Sustainability on Social Networks
Abstract
In this paper, we study a novel paradigm of viral marketing with the goal to sustain the influential effectiveness in the network. We study from real cases such as the Ice Bucket Challenges for the ALS awareness, and figure out the \"easy come and easy go\" phenomenon in the marketing promotion. Such a natural property is fully unexplored in the literature, but it will violate the need of many marketing applications which attempt to receive the perpetual attention and support. We thus highlight the problem of Influential Sustainability, to pursue the long-term and effective influence on the network. Given the set of initial seeds S and a threshold ρ, the goal of Influential Sustainability is to best decide the timing to activate each seed in S so as to maximize the number of iterations in which each iteration will activate the number of inactive nodes more than ρ. The Influential Sustainability problem is challenging due to its #P-hard nature. In addition to the greedy idea, we further present three strategies to heuristically decide the activating timing for each seed. As demonstrated in the empirical study on real data, instead of only providing the flexibility of striking a compromise between the execution efficiency and the resulting quality, these heuristic algorithms can be executed highly efficiently and meanwhile it is able to sustain the longer period which can continuously activate inactive nodes effectively. The results demonstrate their prominent advantage to be practical algorithms for the promising viral marketing paradigm.
Year
DOI
Venue
2015
10.1109/ICDM.2015.129
IEEE International Conference on DataMining
Keywords
Field
DocType
Influential Sustainability,Social Networks,Network Diffusion
Approximation algorithm,Data mining,Viral marketing,Heuristic,Social network,Computer science,Artificial intelligence,Compromise,Empirical research,Market research,Sustainability,Machine learning
Conference
ISSN
Citations 
PageRank 
1550-4786
1
0.36
References 
Authors
18
4
Name
Order
Citations
PageRank
Chien-Wei Chang131.43
Po-An Yang210.70
Ming-Han Lyu310.36
Kun-Ta Chuang425244.61