电子商务翻译
- 格式:doc
- 大小:459.50 KB
- 文档页数:25
Contents lists available at SciVerse ScienceDirect
Electronic Commerce Research and Applications
journal homepage: /locate/ecra
目录列出了可用的华艺SCIENCEDIRECT
电子商务研究与应用
杂志主页:/定位/ ECRA
Discovering target groups in social networking sites: An effective method for maximizing joint influential power
在社交网站中发现目标群体:一种有效的方法为最大限度地发挥联合的影响力
With the tremendous popularity of social networking sites in this era of Web 2.0, increasingly more usersare contributing their comments and opinions about products, people, organizations, and many otherentities. These online comments often have direct influence on consumers’ buying decisions and the pub-lic’s impressions of enterprises. As a result, enterprises have begun to explore the feasibility of usingsocial networking sites as platforms to conduct targeted marking and enterprise reputation managementfor e-commerce and e-business. As indicated from recent marketing research, the joint influential powerof a sm all group of active users could have considerable impact on a large number of consumers’ buyingdecisions and the public’s perception of the capabilities of enterprises. This paper illustrates a novelmethod that can effectively discover the most influential users from social networking sites (SNS). In par-ticular, the general method of mining the influence network from SNS and the computational models ofmathematical programming for discovering the user groups with max joint influential power are pro-posed. The empirical evaluation with real data extracted from social networking sites shows that the pro-posed method can effectively identify the most influential groups when compared to the benchmarkmethods. This study opens the door to effectively conducting targeted marketing and enterprise reputa-tion management on social networking sites.
随着广受欢迎的社交网站在这个Web 2.0时代,越来越多的用户有关产品,人员,组织,和许多其他贡献自己的意见和建议的实体。这些网上的意见往往直接影响消费者的购买决策和酒吧LIC的企业的印象。其结果是,企业已经开始探索使用的可行性社交网站平台,进行有针对性的标志和企业声誉管理电子商务和电子商务。正如从最近的市场调研,联合影响力一小群的活跃用户,可以有相当大的影响消费者的购买大量的决策和公众的认知能力的企业。本文阐述了一种新型的方法,可以有效地发现最有影响力的社交网站(SNS)的用户。在PAR-特别地,开采的影响从SNS的网络的一般方法,和计算模型发现的用户群体最大的联合影响力的数学规划是亲构成的。从社交网站中提取的真实数据的实证评价表明,亲构成的方法可以有效地识别最有影响力的群体相比基准的方法。这项研究打开大门,有效地进行有针对性的营销和企业声誉在社交网站上的重刑管理。
随着Web 2.0时代的到来,社交类网站越来越受到欢迎,越来越多的产品,组织,人员,和许多其他用户把自己的意见和建议实施和添加到这个实体中。这些社交类网站上的意见往往直接影响消费者的购买决策和对于LIC的企业的印象。其导致的结果,就是企业已经开始探索开发和使用自己的可行性社交网站平台,在电子商务中进行有针对性的和对于企业声誉有关的管理。最近的市场调研显示,联合一小群有影响力的活跃用户,可以在相当大的程度上影响消费者的购买决策,文阐述了一种新型的方法,可以有效地发现最有影响力的社交网站(SNS)的用户。特别的,从SNS的网络提起的有一定影响的开发方法,与利用计算机模型发现的最大的且具有强力影响力的用户群体有相互关系。从社交网站中提取的真实且具有实证评价的数据表明,亲构成的方法可以有效地识别最有影响力的群体相比的方法。这项研究有效地打开了有针对性的营销和在社交网站上的管理企业声誉的大门。
1. Introduction
1。介绍