负面评论挖掘的网络口碑危机预警模糊推理
发布时间：2018-11-06 07:24
【摘要】：[目的 /意义]通过挖掘电子商务平台的在线负面评论信息,对网络口碑危机进行模糊预警计算和类型划分,为企业实时监控网络口碑舆情,提高产品正面口碑传播和规避口碑风险提供参考。[方法 /过程]以欧洲消费者满意度模型(ECSI)为基础,从感知质量、感知价值、感知声誉和感知期望4个属性方面构建负面评论网络口碑危机模糊语料词典,结合模糊综合评判方法并改进顾客满意度的四分图模型对网络口碑危机预警进行计算和分类。[结果 /结论]以美团外卖在线评论为例进行实证研究,提出的负面评论网络口碑危机预警计算方法得到了较好的实验检验效果,可为在线产品的网络口碑危机预警提供信息决策。
[Abstract]:[objective / significance] through mining online negative comment information of electronic commerce platform, fuzzy early warning calculation and classification of network word-of-mouth crisis are carried out in order to monitor the public opinion of network word-of-mouth in real time for enterprises. Improve product positive word of mouth spread and circumvent word-of-mouth risk to provide reference. [method / process] based on European consumer satisfaction model (ECSI), a fuzzy corpus dictionary of negative comments on Web-word-of-mouth crisis was constructed from four attributes: perceived quality, perceived value, perceived reputation and perceived expectation. Combined with fuzzy comprehensive evaluation method and improved quadrilateral graph model of customer satisfaction, the early warning of network word-of-mouth crisis is calculated and classified. [results / conclusion] taking Meituan take-out online comment as an example, the method for calculating negative comments' online word-of-mouth crisis is proved to be effective. It can provide information decision-making for online word-of-mouth crisis warning.
【作者单位】： 吉林大学管理学院;长沙师范学院图书馆;
【基金】：国家科技支撑计划子课题“专利信息为科研项目管理提供服务的模型方法”(项目编号:2013BAH21B05)研究成果之一
【分类号】：G206
[Abstract]:[objective / significance] through mining online negative comment information of electronic commerce platform, fuzzy early warning calculation and classification of network word-of-mouth crisis are carried out in order to monitor the public opinion of network word-of-mouth in real time for enterprises. Improve product positive word of mouth spread and circumvent word-of-mouth risk to provide reference. [method / process] based on European consumer satisfaction model (ECSI), a fuzzy corpus dictionary of negative comments on Web-word-of-mouth crisis was constructed from four attributes: perceived quality, perceived value, perceived reputation and perceived expectation. Combined with fuzzy comprehensive evaluation method and improved quadrilateral graph model of customer satisfaction, the early warning of network word-of-mouth crisis is calculated and classified. [results / conclusion] taking Meituan take-out online comment as an example, the method for calculating negative comments' online word-of-mouth crisis is proved to be effective. It can provide information decision-making for online word-of-mouth crisis warning.
【作者单位】： 吉林大学管理学院;长沙师范学院图书馆;
【基金】：国家科技支撑计划子课题“专利信息为科研项目管理提供服务的模型方法”(项目编号:2013BAH21B05)研究成果之一
【分类号】：G206
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