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A Novel Design Science Approach for Integrating Chinese User-Generated Content in Non-Chinese Market Intelligence Completed Research Paper

机译:一种新颖的设计科学方法,用于将中国用户生成内容集成在非中国市场情报中完成的研究论文

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Market research has long relied on reactive means of data gathering, such as questionnaires or focus groups. With the wide-spread use of social media, millions of comments about customer opinions and feedback regarding products and brands are available. However, before using this 'wisdom of the crowd' as a source for marketing research, several challenges have to be tackled: the sheer volume of posts, their unstructured format, and the dozens of different languages used on the internet. All of them make automated usage of this data challenging. In this paper, we draw on dashboard design principles and follow a design science research approach to develop a framework for search, integration, and analysis of cross-language user-generated content. With 'MarketMiner', we implement the framework in the automotive industry by analyzing Chinese auto forums. The results are promising in that MarketMiner can dramatically improve utilization of foreign-language social media content for market intelligence purposes.
机译:市场研究长期以来依赖于数据收集的反应手段,例如问卷或焦点小组。随着社交媒体的广泛应用,有关于客户观点和反馈的数百万条评论,可提供有关产品和品牌的反馈。然而,在利用这种“人群智慧”作为营销研究的来源之前,必须解决几个挑战:界面的庞大数量,非结构化格式以及互联网上使用的数十种不同的语言。所有这些都使得这种数据充满自动使用。在本文中,我们借鉴了仪表板设计原则并遵循设计科学研究方法来开发搜索,集成和分析跨语言用户生成内容的框架。通过“Marketminer”,我们通过分析中国汽车论坛来实施汽车工业的框架。结果在高度上具有很有希望的是,可以大大提高外语社交媒体内容的利用,以获得市场智能目的。

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