TOWARDS EXPLORING WHEN AND WHAT PEOPLE REVIEWED FOR THEIR ONLINE SHOPPING EXPERIENCES  

作　　者：Liangqiang Li Hua Yuan Yu Qian Peiji Shao 

机构地区：[1]School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 611731, China

出　　处：《Journal of Systems Science and Systems Engineering》2018年第3期367-393,共27页系统科学与系统工程学报（英文版）

摘　　要：Web 2.0 technologies have attracted an increasing number of people with various backgrounds to become active online writers and viewers. As a result, exploring reviewers＇ opinions from a huge number of online reviews has become more important and simultaneously more difficult than ever before. In this paper, we first present a methodological framework to study the ＂purchasing-reviewing＂ behavior dynamics of online customers. Then, we propose a review-to-aspect mapping method to explore reviewers＇ opinions from the massive and sparse online reviews. The analytical and experimental results with real data demonstrate that online customers can be sectioned into groups in accordance with their reviewing behaviors and that people within the same group may have similar reviewing motivations and concerns for an online shopping experience.Web 2.0 technologies have attracted an increasing number of people with various backgrounds to become active online writers and viewers. As a result, exploring reviewers＇ opinions from a huge number of online reviews has become more important and simultaneously more difficult than ever before. In this paper, we first present a methodological framework to study the ＂purchasing-reviewing＂ behavior dynamics of online customers. Then, we propose a review-to-aspect mapping method to explore reviewers＇ opinions from the massive and sparse online reviews. The analytical and experimental results with real data demonstrate that online customers can be sectioned into groups in accordance with their reviewing behaviors and that people within the same group may have similar reviewing motivations and concerns for an online shopping experience.

关 键 词：E-COMMERCE online review review dynamics opinion mining 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术] TS976[自动化与计算机技术—计算机科学与技术]