Product selection based on sentiment analysis of online reviews: an intuitionistic fuzzy TODIM method

Author:

Zhang Zhenyu,Guo Jian,Zhang Huirong,Zhou Lixin,Wang Mengjiao

Abstract

AbstractOnline reviews contain a great deal of information about consumers' purchasing preferences, which seriously affects potential consumers' purchasing decisions. Using the online review data to help customers make purchasing decisions has become a concern of customers, which has theoretical and practical application value. Therefore, a product selection model is presented based on sentiment analysis combined with an intuitionistic fuzzy TODIM method. Firstly, the product features are extracted by the Apriori algorithm based on online reviews. The sentiment orientation and intensity of the sentiment words for the product features are identified by the lexicon-based sentiment analysis approach. Next, the sentiment orientation of the product features is represented by an intuitionistic fuzzy value. Then the intuitionistic fuzzy TODIM method is used to determine the ranking results of the alternative products. Finally, the case study of mobile phone selection is given to illustrate the proposed approach. The results show that the proposed method considers the online reviews’ sentiment orientation and intensity and the consumers’ gain and loss in the purchasing product process and is more reasonable than the previous research.

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference40 articles.

1. Naragund GH, Santhosh Kumar KL, Majumdar J (2015) Development of decision making and analysis on customer reviews using sentiment dictionary for human-robot interaction. Int J Adv Res Comput Commun Eng (IJARCCE) 4(8):387–391

2. Zhang Z, Zhang H, Zhou L, Li Y (2021) Analyzing the coevolution of mobile application diffusion and social network: a multi-agent model. Entropy 23(5):521

3. Zhou L, Lin J, Li Y, Zhang Z (2020) Innovation diffusion of mobile applications in social networks: a multi-agent system. Sustainability 12(7):2884

4. Zhang K, Narayanan R, Choudhary AN (2010) Voice of the customers: mining online customer reviews for product feature-based ranking. WOSN 10:11–11

5. Zhang K, Cheng Y, Liao WK, Choudhary A (2011, August) Mining millions of reviews: a technique to rank products based on importance of reviews. In: Proceedings of the 13th international conference on electronic commerce, pp 1–8

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3