Algorithm of Seed Selection for Maximizing the Spread of Mutual-Influence Preferences in Social Networks

• Main Author: 鄭如意
• Other Authors: 蔡明哲
• Format: Others
• Language: en_US
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/54538773435850974322

碩士 === 國立清華大學 === 通訊工程研究所 === 102 === Marketing is convenient, low-cost, and beneficial for small companies to expand their customers through social networks. In the literature, many studies address the influence maximization problem which selects initial users (seeds) to spread the product information such that the number of users receiving the product information is maximized. However, these schemes do not take the social factors (e.g., the beliefs of other persons) into account for predicting the user’s behavioral intention. In this paper, we fill this gap by proposing a new variant of the influence maximization problem (BSS) which asks for a set of seeds with the total cost not greater than a given budget such that the total behavioral intentions of the users influenced is maximized. In addition, we also propose an algorithm for the {BSS} problem. We conduct simulations to evaluate the performance of our algorithm using real traces. Experimental results show that our algorithm outperforms several greedy algorithms.