@inproceedings{a3e3402cb47943148357fd350c44c9c8,
title = "Uncovering the Key Factors of Consumer Trust in E-Commerce: A Comprehensive Study of Review-Based Factor Extraction Using GPT-Based Model",
abstract = "Online reviews have become a critical source of information for businesses to understand customer sentiment. In this study, a subset of 1,499 reviews was analyzed to identify factors that influence consumer trust. The research methodology used a GPT-based model to extract factors affecting consumer trust, and its reliability and trustworthiness were evaluated by comparing it with reviewers' judgments for each customer review. Our findings revealed that various factors significantly impact consumer evaluations and trust, with product quality being the most critical factor, followed by satisfaction with Size/Fit. Our study sheds light on the effectiveness and validity of GPT-based models in opinion mining, which can help businesses better understand consumer sentiments. By recognizing the dynamic nature of consumer feedback, businesses can improve their products, services, and consumer trust.",
keywords = "artifcial intelligence, Consumer trust, e-commerce, GPT-3.5, natural language processing, sentiment analysis",
author = "Alkhalil, \{Bandar F.\} and Yu Zhuang and Mursi, \{Khalid T.\} and Aseeri, \{Ahmad O.\}",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 3rd IEEE International Conference on Computing and Machine Intelligence, ICMI 2024 ; Conference date: 13-04-2024 Through 14-04-2024",
year = "2024",
doi = "10.1109/ICMI60790.2024.10585824",
language = "English",
series = "2024 IEEE 3rd International Conference on Computing and Machine Intelligence, ICMI 2024 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Ahmed Abdelgawad and Akhtar Jamil and Hameed, \{Alaa Ali\}",
booktitle = "2024 IEEE 3rd International Conference on Computing and Machine Intelligence, ICMI 2024 - Proceedings",
address = "United States",
}