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Discovering the influential users oriented to viral marketing based on online social networks

机译：基于在线社交网络发现面向病毒式营销的有影响力的用户

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摘要

The target of viral marketing on the platform of popular online social networks is to rapidly propagate marketing information at lower cost and increase sales, in which a key problem is how to precisely discover the most influential users in the process of information diffusion. A novel method is proposed in this paper for helping companies to identify such users as seeds to maximize information diffusion in the viral marketing. Firstly, the user trust network oriented to viral marketing and users' combined interest degree in the network including isolated users are extensively defined. Next, we construct a model considering the time factor to simulate the process of information diffusion in viral marketing and propose a dynamic algorithm description. Finally, experiments are conducted with a real dataset extracted from the famous SNS website Epinions. The experimental results indicate that the proposed algorithm has better scalability and is less time-consuming. Compared with the classical model, the proposed algorithm achieved a better performance than does the classical method on the two aspects of network coverage rate and time-consumption in our four sub-datasets.
机译：在流行的在线社交网络平台上，病毒式营销的目标是以较低的成本快速传播营销信息并增加销售，其中的关键问题是如何在信息传播过程中准确地发现最具影响力的用户。本文提出了一种新颖的方法，以帮助公司识别此类用户作为种子，从而在病毒性营销中最大化信息传播。首先，广泛定义了面向病毒式营销的用户信任网络和网络中包括孤立用户在内的用户的综合兴趣度。接下来，我们构造一个考虑时间因素的模型来模拟病毒式营销中的信息传播过程，并提出动态算法描述。最后，使用从著名的SNS网站Epinions中提取的真实数据集进行实验。实验结果表明，该算法具有较好的可扩展性，并且耗时少。与经典模型相比，该算法在四个子数据集的网络覆盖率和时间消耗两个方面都比经典方法具有更好的性能。

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