Chen Kuan-Yu, Liao Hsiu-Yu, Chen Jyun-Hung, Liu Duen-Ren
Institute of Information Management, National Chiao Tung University, Hsinchu 30010, Taiwan.
ScientificWorldJournal. 2015;2015:523174. doi: 10.1155/2015/523174. Epub 2015 Mar 5.
Virtual worlds (VWs) are computer-simulated environments which allow users to create their own virtual character as an avatar. With the rapidly growing user volume in VWs, platform providers launch virtual goods in haste and stampede users to increase sales revenue. However, the rapidity of development incurs virtual unrelated items which will be difficult to remarket. It not only wastes virtual global companies' intelligence resources, but also makes it difficult for users to find suitable virtual goods fit for their virtual home in daily virtual life. In the VWs, users decorate their houses, visit others' homes, create families, host parties, and so forth. Users establish their social life circles through these activities. This research proposes a novel virtual goods recommendation method based on these social interactions. The contact strength and contact influence result from interactions with social neighbors and influence users' buying intention. Our research highlights the importance of social interactions in virtual goods recommendation. The experiment's data were retrieved from an online VW platform, and the results show that the proposed method, considering social interactions and social life circle, has better performance than existing recommendation methods.
虚拟世界（VWs）是计算机模拟环境，允许用户创建自己的虚拟角色作为化身。随着虚拟世界用户数量的迅速增长，平台提供商匆忙推出虚拟商品并哄骗用户以增加销售收入。然而，开发的快速性带来了虚拟无关物品，这些物品将难以重新销售。这不仅浪费了虚拟全球公司的智力资源，也使得用户在日常虚拟生活中难以找到适合其虚拟家园的合适虚拟商品。在虚拟世界中，用户装饰他们的房子、参观他人的家、创建家庭、举办派对等等。用户通过这些活动建立他们的社交生活圈。本研究基于这些社交互动提出了一种新颖的虚拟商品推荐方法。与社交邻居的互动产生的联系强度和联系影响会影响用户的购买意愿。我们的研究强调了社交互动在虚拟商品推荐中的重要性。实验数据取自一个在线虚拟世界平台，结果表明，考虑社交互动和社交生活圈的所提方法比现有推荐方法具有更好的性能。
