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随着各类社交网站和社会化媒体网站的兴起,海量且相互关联的数据留存在互联网中,基于复杂网络理论的大数据分析技术成为挖掘这些数据并用以企业管理决策的重要工具。以科学计量学方法为基础,系统论述流行趋势预测技术的演进路径,重点分析现代服流装行趋势预测技术如何从互联网中挖掘海量消费者行为信息,特别是从网络科学技术角度包括网络数据挖掘、行为动力学、网络信息传播等角度提出获取、评估、检测、预警和引导网络流行趋势的研究思路,从而为后期进行相应的实证研究、构建网络流行趋势响应方法提供理论基础。
With the rise of various types of social networking sites and social media websites, vast amounts of interdependent data remain in the Internet. Based on the theory of complex networks, big data analysis technology has become an important tool for mining these data and making decisions for business management. Based on the scientific metrology method, this paper systematically discusses the evolutionary path of the trend forecasting technology, and focuses on how modern trend forecasting technology of clothes loading lines can tap the massive consumer behavior information from the Internet, especially from the network science and technology perspective, including network data mining , Behavioral dynamics and network information dissemination, this paper puts forward the research ideas of acquiring, assessing, detecting, early warning and guiding the network trend, and provides the theoretical basis for the corresponding empirical research in the later stage and the construction of the network trend response method.