Proceedings of the 17th International Conference on Data Engineering
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
On domination game analysis for microeconomic data mining
ACM Transactions on Knowledge Discovery from Data (TKDD)
Scalable Influence Maximization in Social Networks under the Linear Threshold Model
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
Maximizing product adoption in social networks
Proceedings of the fifth ACM international conference on Web search and data mining
| Hi-index | 0.00 |
In this paper, we propose a new type of market model called the social domination game model. Given a set C of customers and a set P of products, this model simulates market competition among P and estimates market shares, considering both the dominance relation between C and P and the influence relation among the members of C. With this model, we propose a greedy product positioning algorithm for designing a new product that approximately maximizes market share. Our experimental results show that the proposed algorithm creates a new product gaining up to 97.5% market share of the best product's market share obtained by the exact method, while significantly outperforming the exact method in terms of running time, i.e., by up to two orders of magnitude.