Marketing Resource Allocation in Dynamic Social Networks

• Main Author: 朱禾民
• Other Authors: 楊婉秀
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/15722466414456074250

碩士 === 國立彰化師範大學 === 資訊管理學系所 === 95 === Viral marketing takes advantage of networks of influence among customers to inexpensively promote a product. A premise of viral marketing is that by initially targeting a few influential members of the network we can trigger a cascade of influence by which friends will recommend the product to other friends. Hence an important question is how to choose the few key individuals to use for seeding the process. In previous works, this question was investigated under the assumption of static network. In this thesis, we propose a novel approach which utilizes the concepts of genetic algorithm to find a few individuals which can maximize the spread of influence in dynamic networks. We evaluate the proposed approach by using real-world co-authorship data. The experimental results show that our approach does well at finding the few key individuals for viral marketing.