Enabling Social Commerce - A New Form of E-commerce that Leverages Social Ties Between Users

IBM将社交商务定义为“将口碑的概念应用于电子商务”。当用户在线互动时，她有意或无意地传播了有关产品或品牌的信息；因此，她的在线社区成员可以在购买决策中利用她的意见。由于口碑依赖于社会关系，它正成为社交媒体和电子商务网站的首选营销策略。对于商业和学术界来说，有必要了解社交商务，研究支持它的平台的设计，并调查这些平台固有的社会联系，所有这些都以满足企业和消费者的方式进行。这项建议的目标是双重的。首先，我们将研究社交电商平台的设计。这类平台有两类：一类是在社交媒体平台上添加“商务”功能的平台（例如，在Facebook上启用电子商务的应用程序）；还有一些在电子商务平台上增加了“社交”功能（例如，在亚马逊上有一个按钮，让顾客与她的Facebook朋友“分享”她的购买）。我们将研究以高效和有效的方式开发社交商务平台的设计框架和流程。其次，我们将研究预测关系（又名链接）形成的算法，以及那些在社交商务平台上检测社区的算法。这一建议将产生经济影响，使社交商务成为可能；通过创造和使用新的方法来解决复杂的问题，如创新的社交商务设计和更准确有效的社交关系预测和社区检测算法，从而产生科学影响。

Social commerce is defined by IBM as "the concept of word-of-mouth applied to e-commerce". When a user interacts online, she knowingly or unknowingly spreads the word about a product or brand; hence members of her online community can leverage her opinions in their purchase decisions. As word-of-mouth relies on social ties, it is becoming the marketing strategy of choice deployed on social media and e-commerce websites. For business and academia there is a need to understand social commerce, to study the design of platforms that support it, and to investigate the social ties that are inherent to these platforms, all in a way that satisfies businesses and consumers. The objectives of this proposal are twofold. First, we will study the design of social commerce platforms. There are two categories of such platforms: those that add "commerce" features to social media platforms (e.g., applications that enable e-commerce on Facebook); and those that add "social" features to e-commerce platforms (e.g., having a button on Amazon for the customer to "share" her purchases with her Facebook friends). We will investigate design frameworks and processes for developing social commerce platforms in an efficient and effective way. Second, we will study algorithms that predict the formation of ties (aka links) and those that detect communities on social commerce platforms. This proposal will have an economic impact by enabling social commerce; and a scientific impact by creating and using new methodologies to address complex issues such as innovative social commerce design and more accurate and efficient algorithms for social tie prediction and community detection.