Analyzing customer reviews with abstractive summarization and sentiment analysis: a software review

被引：0
|
作者：
Hakimi, Mohammed [1 ]
Ul Haq, Mirza Amin [2 ,5 ]
Ghouri, Arsalan Mujahid [3 ]
Valette-Florence, Pierre [4 ]
机构：
[1] Univ Prince Mugrin, Madinah, Saudi Arabia
[2] Ziauddin Univ, Karachi, Pakistan
[3] London South Bank Univ, London, England
[4] Int Univ Monaco, MC-98000 Le Stella, Monaco
[5] UCSI Univ, Kuala Lumpur, Malaysia
来源：
JOURNAL OF MARKETING ANALYTICS | 2025年
关键词：
Customer reviews; Abstractive summary; Sentiment analysis; Artificial intelligence; Machine learning; EXPERIENCE MANAGEMENT; BRAND; POWER;
D O I：
10.1057/s41270-025-00377-8
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
Customer reviews significantly influence consumer decisions and business strategies, requiring more advanced analytical tools to collect these valuable insights. This study examines a recent online application that analyzes customer reviews using abstractive summarization and sentiment analysis. The application allows users to monitor customer feedback through abstractive summaries and sentiment scores. The reviews can be directly pasted or uploaded via a text file for analysis. This article assesses the application across five different use cases, addressing challenges related to satisfaction, mixed reviews, recovery strategies, dissatisfaction, and sarcastic reviews. The research advocates ongoing exploration and refinement of artificial intelligence and machine learning applications, emphasizing the synergistic potential of abstractive summarization and sentiment analysis for effectively monitoring customer reviews and preferences. This practical tool empowers businesses and practitioners to make data-driven decisions based on customer feedback. Access to the application: https://mahaq.pythonanywhere.com/.
引用
收藏
页数：15
相关论文
共 50 条
  • [21] Sentiment Analysis and classification for Software as a Service Reviews
    Alkalbani, Asma Musabah
    Ghamry, Ahmed Mohamed
    Hussain, Farookh Khadeer
    Hussain, Omar Khadeer
    IEEE 30TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS IEEE AINA 2016, 2016, : 53 - 58
  • [22] Objective and neutral summarization of customer reviews
    Carichon, Florian
    Ngouma, Chrys
    Liu, Bang
    Caporossi, Gilles
    EXPERT SYSTEMS WITH APPLICATIONS, 2024, 255
  • [23] Automatic summarization of online customer reviews
    Zhan, Jiaming
    Loh, Han Tong
    Liu, Ying
    WEBIST 2007: PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON WEB INFORMATION SYSTEMS AND TECHNOLOGIES, VOL SEBEG/EL: SOCIETY, E-BUSINESS AND E-GOVERNMENT, E-LEARNING, 2007, : 5 - +
  • [24] Text Summarization for Thai Food Reviews using Simplified Sentiment Analysis
    Porntrakoon, Paitoon
    Moemeng, Chayapol
    Santiprabhob, Pratit
    2021 18TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER SCIENCE AND SOFTWARE ENGINEERING (JCSSE-2021), 2021,
  • [25] Sentiment Analysis of Product Reviews: A Review
    Shivaprasad, T. K.
    Shetty, Jyothi
    PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON INVENTIVE COMMUNICATION AND COMPUTATIONAL TECHNOLOGIES (ICICCT), 2017, : 298 - 303
  • [26] ALS-MRS: Incorporating aspect-level sentiment for abstractive multi-review summarization
    Zhao, Qingjuan
    Niu, Jianwei
    Liu, Xuefeng
    KNOWLEDGE-BASED SYSTEMS, 2022, 258
  • [27] Modeling content and structure for abstractive review summarization
    Gerani, Shima
    Carenini, Giuseppe
    Ng, Raymond T.
    COMPUTER SPEECH AND LANGUAGE, 2019, 53 : 302 - 331
  • [28] ALS-MRS: Incorporating aspect-level sentiment for abstractive multi-review summarization
    Zhao, Qingjuan
    Niu, Jianwei
    Liu, Xuefeng
    Knowledge-Based Systems, 2022, 258
  • [29] Sentiment Analysis on Customer Reviews using Convolutional Neural Network
    Tammina, Srikanth
    Annareddy, Sunil
    2020 INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND INFORMATICS (ICCCI - 2020), 2020, : 518 - 523
  • [30] Sentiment Analysis of Customer Reviews: Balanced versus Unbalanced Datasets
    Burns, Nicola
    Bi, Yaxin
    Wang, Hui
    Anderson, Terry
    KNOWLEDGE-BASED AND INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT I: 15TH INTERNATIONAL CONFERENCE, KES 2011, 2011, 6881 : 161 - 170
12345