A Novel Product Ranking Approach Considering Sentiment Intensity Distribution of Online Reviews

被引：0
|
作者：
Gu, Sheng-qiang [1 ]
Liu, Shi-tong [2 ]
Liu, Yong [2 ]
Ding, Jia-ming [2 ]
机构：
[1] Nanjing Univ Aeronaut & Astronaut, Sch Econ & Management, Nanjing 211106, Peoples R China
[2] Jiangnan Univ, Sch Business, Lihu Lake Rd 1800, Wuxi 214122, Jiangsu, Peoples R China
来源：
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS | 2024年 / 17卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Product ranking; Online review; Sentiment analysis; Sentiment intensity distribution; Grey incidence analysis; CUSTOMER REVIEWS;
D O I：
10.1007/s44196-024-00688-1
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Online reviews of products have a significant impact on consumers' purchasing decisions, making it important for both platform retailers and consumers to rank products, and eventually purchase products. With respect to the problem of product ranking that consists of the information contained in online reviews; by considering the sentiment intensity distribution of online reviews, we establish a fine-grained sentiment intensity analysis and then exploit grey incidence analysis and TOPSIS to establish a multi-attribute approach for product ranking. Finally, a case study of laptop purchases verifies the applicability and effectiveness of the proposed approach.
引用
收藏
页数：18
相关论文
共 50 条
  • [21] Identifying Sentiment-Dependent Product Features from Online Reviews
    Suryadi, Dedy
    Kim, Harrison M.
    DESIGN COMPUTING AND COGNITION '16, 2017, : 685 - 701
  • [22] Learning sentiment dependent Bayesian network classifier for online product reviews
    Orimaye, Sylvester Olubolu
    Pang, Zi Yang
    Setiawan, Alvino Mandala Putra
    Informatica (Slovenia), 2016, 40 (02): : 225 - 235
  • [23] Exploring fine-grained sentiment values in online product reviews
    Teh, Phoey Lee
    Rayson, Paul
    Pak, Irina
    Piao, Scott
    2015 IEEE CONFERENCE ON OPEN SYSTEMS (ICOS), 2015, : 114 - 118
  • [24] Learning Sentiment Dependent Bayesian Network Classifier for Online Product Reviews
    Orimaye, Sylvester Olubolu
    Pang, Zi Yang
    Setiawan, Alvino Mandala Putra
    INFORMATICA-JOURNAL OF COMPUTING AND INFORMATICS, 2016, 40 (02): : 225 - 235
  • [25] Online Reviews Sentiment Analysis and Product Feature Improvement with Deep Learning
    Cao, Jihua
    Li, Jie
    Yin, Miao
    Wang, Yunfeng
    ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING, 2023, 22 (08)
  • [26] Personalized Ranking of Online Reviews Based on Consumer Preferences in Product Features
    Dash, Anupam
    Zhang, Dongsong
    Zhou, Lina
    INTERNATIONAL JOURNAL OF ELECTRONIC COMMERCE, 2021, 25 (01) : 29 - 50
  • [27] Ranking Tourist Attractions through Online Reviews: A Novel Method with Intuitionistic and Hesitant Fuzzy Information Based on Sentiment Analysis
    Yong Qin
    Xinxin Wang
    Zeshui Xu
    International Journal of Fuzzy Systems, 2022, 24 : 755 - 777
  • [28] A Hotel Ranking Model Through Online Reviews with Aspect-Based Sentiment Analysis
    You, Tian-Hui
    Tao, Ling-Ling
    Cambria, Erik
    INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING, 2023, 22 (01) : 89 - 113
  • [29] Study of Automatic Extraction, Classification, and Ranking of Product Aspects Based on Sentiment Analysis of Reviews
    Rafi, Muhammad
    Farooq, M. Rafay
    Noman, Usama
    Farooq, Abdul Rehman
    Khatri, Umair Ali
    WORLD CONGRESS ON ENGINEERING AND COMPUTER SCIENCE, WCECS 2015, VOL II, 2015, : 781 - 786
  • [30] Study of Automatic Extraction, Classification, and Ranking of Product Aspects Based on Sentiment Analysis of Reviews
    Rafi, Muhammad
    Noman, Usama
    Farooq, Muhammad Rafay
    Farooq, Abdul Rehman
    Khatri, Umair Ali
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2015, 6 (10) : 246 - 252
12345