Detecting unexpected correlation between a current topic and products from buzz marketing sites
Detecting unexpected correlation between a current topic and products from buzz marketing sites
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检测当前主题与热门营销网站的产品之间的意外相关性
DOI：
10.1007/978-3-642-25731-5_13
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
and Y. Shirota
中科院分区：
文献类型：
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作者：
T. Hashimoto;T. Kuboyama;and Y. Shirota
本文提出了一种在buzz营销网站中检测当前话题和产品口碑之间的意外相关性的方法，这将是营销分析新方法的一部分。例如，2009年，超级流感病毒对全球各种产品营销领域产生了重大影响。在热门营销网站上，有很多关于“流感”的口口相传。我们可以很容易地期望“空气净化器”与“流感”相关联，空气净化器的出货量随着流感的流行而增长。另一方面，“流感”和“相机”之间的联系是不容易预料到的。然而，在日本，由于流感流行导致的旅行、体育节或其他活动取消，消费者不愿购买数码相机等不可预见的行为已经出现，“流感”与“相机”之间存在很强的相关性。检测这些不可预见的消费者行为对今天的营销分析具有重要意义。为了检测这种非预期关系，本文采用了动态时间规整技术。我们提出的方法计算当前主题与来自口碑营销网站的未指定产品之间的时间序列相关性，并找到与当前主题具有意外相关性的候选产品。为了评估该方法的有效性，还显示了当前主题（“流感”）和产品（“空气净化器”、“相机”、“汽车”等）的实验结果。通过检测buzz营销网站的意外相关性，可以进一步分析意外的消费者行为。
This paper proposes a method to detect unexpected correlation from between a current topic and products word of mouth in buzz marketing sites, which will be part of a new approach to marketing analysis. For example, in 2009, the super-flu virus spawned significant effects on various product marketing domains around the globe. In buzz marketing sites, there had been a lot of word of mouth about the "flu." We could easily expect an "air purifier" to be correlated to the "flu" and air purifiers’ shipments had grown according to the epidemic of flu. On the other hand, the relatedness between the "flu" and a "camera" could not be easily expected. However, in Japan, consumers’ unforeseen behavior like the reluctance to buy digital cameras because of cancellations of a trip, a PE festival or other events caused by the epidemic of flu had appeared, and a strong correlation between the "flu" and "camera" had been found. Detecting these unforeseen consumers’ behavior is significant for today’s marketing analysis. In order to detect such unexpected relations, this paper applies the dynamic time warping techniques. Our proposed method computes time series correlations between a current topic and unspecified products from word of mouth of buzz marketing sites, and finds product candidates which have unexpected correlation with a current topic. To evaluate the effectiveness of the method, the experimental results for the current topic ("flu") and products ("air purifier", "camera", "car", etc.) are shown as well. By detecting unexpected relatedness from buzz marketing sites, unforeseen consumer behaviors can be further analyzed.