【摘要】：[目的 /意義]通過挖掘電子商務平臺的在線負面評論信息,對網(wǎng)絡口碑危機進行模糊預警計算和類型劃分,為企業(yè)實時監(jiān)控網(wǎng)絡口碑輿情,提高產(chǎn)品正面口碑傳播和規(guī)避口碑風險提供參考。[方法 /過程]以歐洲消費者滿意度模型(ECSI)為基礎,從感知質(zhì)量、感知價值、感知聲譽和感知期望4個屬性方面構建負面評論網(wǎng)絡口碑危機模糊語料詞典,結合模糊綜合評判方法并改進顧客滿意度的四分圖模型對網(wǎng)絡口碑危機預警進行計算和分類。[結果 /結論]以美團外賣在線評論為例進行實證研究,提出的負面評論網(wǎng)絡口碑危機預警計算方法得到了較好的實驗檢驗效果,可為在線產(chǎn)品的網(wǎng)絡口碑危機預警提供信息決策。
[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.
【作者單位】： 吉林大學管理學院;長沙師范學院圖書館;
【基金】：國家科技支撐計劃子課題“專利信息為科研項目管理提供服務的模型方法”(項目編號:2013BAH21B05)研究成果之一
【分類號】：G206

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