摘要
从微观尺度出发,利用在线评论大数据对景区的网络口碑进行研究。选取张家界国家森林公园为研究对象,从大数据视角入手,以新浪微博和马蜂窝等平台为信息中介,抓取并研究案例相关评论数据,构建朴素贝叶斯情感分类器对张家界国家森林公园的网络口碑进行分析。结果表明,与近几年相比,研究案例在2018年的网络口碑有一定程度的下降,与现实情况吻合;此外评论的分类准确率、召回率以及F值等评价指标均在90%左右,研究结果和研究方法对分析景区的网络口碑具有参考价值。
This paper conducts research on Internet Word of Mouth(IWOM)in scenic spots based on the big data of online reviews from the micro perspective.Taking Zhangjiajie National Forest Park as a case study and based on big data of online reviews from Sina Weibo and Mafengwo Website,it captures and studies on the online reviews related to the case,and applies Naive Bayesian Classifier to analyze the IWOM of Zhangjiajie National Forest Park.Experimental results show that,compared with recent years,the IWOM of Zhangjiajie National Forest Park declined in 2018,which was consistent with the reality.In addition,the average precision,recall and F-test of the classification of the reviews are all at around 90%,which means the research conclusions and proposed methods can be referred in analyzing IWOM of scenic spots.
作者
肖文杰
张艳芳
XIAO Wen-jie;ZHANG Yan-fang(Tourism and Administrative Engineering College,Jishou University,Zhangjiajie 427000,China)
出处
《软件导刊》
2019年第11期121-125,共5页
Software Guide
基金
湖南省教育厅科学研究一般项目(17C1325)
作者简介
肖文杰(1985-),男,硕士,吉首大学旅游与管理学院讲师,研究方向为旅游大数据挖掘;张艳芳(1997-),女,吉首大学旅游与管理工程学院学生,研究方向为电子商务与物流管理。
