数据驱动的未来场景:基于社交媒体数据的智能家居服务体验预测

Zhiyong Fu, Anna Barbara, P. Scupelli, Yanru Lyu, Y. Cheng, S. Sul
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引用次数: 0

摘要

探索未来情景可以从长远的角度考虑子孙后代和社会。期货三角是一种用于描绘未来情景的方法。一般来说,期货三角利用定性研究方法收集弱信号。然而,定性采集微弱信号受到数据量小和人工数据分析误差的限制。为了克服这些限制,本研究提出了数据驱动的未来情景方法。该方法通过语义网络分析,将社交网络中存在的大量社会感知作为弱信号进行分析。使用我们提出的数据驱动方法,研究人员可以定量地收集期货三角的微弱信号。为了验证所提出方法的适用性,我们对中国智能家居服务体验进行了案例研究。该数据集由中国社交媒体平台微博上2421条包含“智能家居体验”关键词的帖子组成。利用所提出的方法构建了三种未来情景。结果表明了所提方法的可行性。数据驱动的未来情景方法具有定量分析大量利益相关者数据的优势,为期货三角提供微弱信号。我们建议将数据驱动的未来情景方法作为补充方法,与传统的期货三角方法相结合,全面探索未来情景。
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Data-Driven Futuristic Scenarios: Smart Home Service Experience Foresight Based on Social Media Data
Exploring future scenarios can consider future generations and society from a long-term perspective. A Futures Triangle is an approach used for mapping future scenarios. In general, the Futures Triangle collects weak signals using qualitative research methods. However, collecting weak signals qualitatively is limited by its small data size and manual data analysis errors. To overcome those limitations, this study proposes the data-driven futuristic scenario approach. This approach analyzes a large number of social perceptions existing in social networks as weak signals via semantic network analysis. Using our proposed data-driven approach, researchers can quantitatively collect weak signals for a Futures Triangle. To verify the applicability of the proposed method, we conducted a case study on the Chinese smart home service experience. The dataset consists of 2421 posts containing the keyword “smart home experience” on the Chinese social media platform Weibo. Three future scenarios were constructed using the proposed method. The results demonstrate the feasibility of the proposed methodology. The data-driven futuristic scenario approach has the advantage of quantitatively analyzing a large amount of stakeholder data to provide weak signals for the Futures Triangle. We suggest that the data-driven futuristic scenario approach serves as a supplementary method, combined with the traditional Futures Triangle approach, to comprehensively explore future scenarios.
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来源期刊
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审稿时长
9 weeks
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