• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Creativity and innovation management >Digital anthropology as method for lead user identification from unstructured big data
【24h】

Digital anthropology as method for lead user identification from unstructured big data

机译：数字人类学作为从非结构化大数据中识别主要用户的方法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper focuses on lead user identification in an open data context through the principles of digital anthropology (DA). The approach is demonstrated using a case study from the entertainment industry: the festival of Tomorrowland. Following the principles of DA, the specific data structure of the case selected is studied. This structure follows the tribal roles of Cova and Cova, which are then compared with the lead user characteristics of Belz and Baumbach. The different characteristics and roles are used afterwards to establish the user types that may be found in the big data set of the case study. Unlike earlier methods, such as netnography, which focuses on a specific user type as the main source of insights, our results show that DA requires a change of focus from specific individuals to groups of individuals with the capacity to produce the insights of a lead user. DA shows how all the roles in the data structure present different possibilities for innovation. The application of DA to big data enables the extension of analysis to whole populations instead of specific samples, bringing about new possibilities to model and extract the insights of consumers publicly exposed in the digital media.
机译：本文着重通过数字人类学（DA）原理在开放数据上下文中识别主要用户。娱乐业的一个案例研究证明了这种方法：明日节。遵循DA的原则，研究所选案例的特定数据结构。该结构遵循Cova和Cova的部落角色，然后将其与Belz和Baumbach的主要用户特征进行比较。之后使用不同的特征和角色来建立在案例研究的大数据集中可以找到的用户类型。与早期的方法（如netnography）不同，它只关注特定用户类型作为见解的主要来源，我们的结果表明，DA需要将关注点从特定个人更改为有能力产生主要用户见解的个人组。 DA显示了数据结构中的所有角色如何为创新提供了不同的可能性。将DA应用于大数据可以将分析扩展到整个人群，而不是特定的样本，从而为建模和提取在数字媒体中公开曝光的消费者的见解提供了新的可能性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号