基于文本挖掘的在线用户追加评论内容情报研究——以京东商城手机评论数据为例  

Research on Information of Online Users'Additional Comments Based on Text Mining——Take the Mobile Phone Review Data of Jingdong Mall as an Example

作　　者：张艳丰[1] 王羽西 彭丽徽[1] 刘亚丽 Zhang Yanfeng;Wang Yuxi;Peng Lihui;Liu Yali(School of Public Management,Xiangtan University,Xiangtan 411105,China)

机构地区：[1]湘潭大学公共管理学院,湖南湘潭411105

出　　处：《现代情报》2020年第9期96-105,共10页Journal of Modern Information

基　　金：湖南省教育厅优秀青年项目“在线用户评论行为时间异质性规律研究”(项目编号:18B071)。

摘　　要：[目的/意义]通过对在线用户追加评论文本内容进行挖掘,有助于电商企业掌握在线用户发布后续评论的普遍时间规律,可以根据追加评论内容特征属性来指导厂家进行商品改进以及辅助用户的购买决策行为。[方法/过程]从内容维度,通过语义特征分析、情感特征分析、词频共现分析和时间特征分析对在线用户追加评论文本分别进行文本内容挖掘。[结果/结论]阐述了在线用户追加评论的内容情报特征及其与初始评论文本语义的关联与差异,揭示了在线用户追加评论行为时间滞后符合幂率分布特征。[Purpose/Significance]Mining the content of online users'additional comments will help e-commerce enterprises to grasp the general rule of time for online users to publish follow-up comments,and can guide manufacturers to improve their products and assist users to make purchasing decisions according to the characteristics of additional comments.[Method/Process]From the content dimension,text content mining of online users'additional comment texts was carried out through semantic feature analysis,emotional feature analysis,word frequency co-occurrence analysis and time feature analysis.[Result/Conclusion]This paper expounded the content information characteristics of online users'supplementary comments and their relationship and difference with the semantics of the original comments,and revealed that the time lag of online users'supplementary comments conforms to the power distribution characteristics.

关 键 词：在线用户评论 追加评论 内容情报 文本挖掘 数据挖掘 电子商务 京东商城 

分 类 号：G250.2[文化科学—图书馆学]