使用K-core, M-core和Km-core方法分析Facebook用户粘性图表

Thidawan Klaysri
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引用次数: 0

摘要

从用户对版主帖子的反应来看,一个品牌的Facebook粉丝页面的用户参与度可以被解释为一个网络。本文用不同形式的图表示了两家连锁超市驿站所连接的消费者网络。本文提出了一个图分析框架,该框架采用社会网络分析的概念来考察图的结构。图过滤方法,k-core, m-core或m-slice和km-core,前核心的组合,被用来检查客户参与行为,识别和过滤消费者社区。对于这两个超市品牌来说,大多数顾客对广告和促销职位的态度都是积极的。他们的客户参与行为相似,大多数客户都被一条折扣促销广告所吸引,超过90%,遵循消费者程度门槛和共同反应帖子的幂律。大约有3%的消费者同时使用这两个品牌。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Facebook Customer Engagement Graph Analysis Using K-core, M-core and Km-core Methods
Customer engagement in Facebook fan page of a brand can be rationalized as a network from customer reactions towards the moderator postings. In this paper the network of consumers connected by the posts of two supermarket chains are represented in different forms of graphs. Here a graph analytic framework, which adopts the concept of Social Network Analysis to examine the structure of the graphs, is presented. The graph filtering methods, k-core, m-core or m-slice and km-core, a combination of the former cores, are utilized to examine the customer engagement behavior, to identify and to filter the consumer communities. For both supermarket brands, most of the customer attitudes toward the advertising and promotion posts are positive. Their customer engagement behaviors are similar, in that the majority of customers are engaged by a single post advertising a discount promotion, greater than 90%, following power-laws with respect to the threshold of consumer degree and co-reaction posts. There are around 3% of customers consuming both brands.
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