产品垃圾评论识别研究综述

doi:10.19722/j.cnki.1008-7729.2019.0101

北京邮电大学学报(社科版) ›› 2019, Vol. 21 ›› Issue (3): 71-79.doi: 10.19722/j.cnki.1008-7729.2019.0101

产品垃圾评论识别研究综述

北京邮电大学经济管理学院, 北京100876

出版日期:2019-06-30
基金资助:
国家自然科学基金项目（71874018） (71471019)

Literature Review on Identification of Product Spam Comments

School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, China

Online:2019-06-30

摘要/Abstract

摘要：
摘要: 着重梳理当前产品垃圾评论识别的国内外研究，总结研究特点与不足，发掘发展趋势。在中国知网、Web of Science上以“虚假评论”“review spam”等为关键词检索并筛选得到54篇国内外相关文献，采用文献分析法对其进行分类分析，重点阐述研究在识别特征和识别方法方面的优化创新，以及针对垃圾评论、垃圾评论发布者、发布群体等不同识别对象的方法差异。研究发现，当前垃圾评论识别的相关成果可以分为基于评论内容的方法和基于评论结构、评论者、被评论产品的方法，在未来的垃圾评论识别中，应根据数据集的特点，提取有效识别特征，选择优化识别方法。

关键词: 在线评论, 垃圾评论识别, 文本挖掘, 综述

Abstract: The current research on identification of product spam comments at home and abroad is discussed and the characteristics of the research methods, deficiencies and the development trend are summarized Fifty-four related literatures were retrieved and screened on CNKI and Web of Science by using the keywords of “fake review” and “review spam” Literature analysis is used to classify and analyze the literature The optimization and innovation of research on identification features and identification methods, as well as the differences of identification methods for different objects such as spam comments, spam reviewers are emphasized It is found that the methods current research used can be divided into content-based methods and methods based on the structure of comments, reviewers and commented products In the future research, effective identification features with multi-dimensions should be picked up and methods should be optimized according to the characteristics of data sets

Key words: online comment, spam comment identification, text mining, literature review

中图分类号:

C931

万岩,王雅璐. 产品垃圾评论识别研究综述[J]. 北京邮电大学学报(社科版), 2019, 21(3): 71-79.

WAN Yan, WANG Ya-lu. Literature Review on Identification of Product Spam Comments[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2019, 21(3): 71-79.

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产品垃圾评论识别研究综述

Literature Review on Identification of Product Spam Comments

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