Customer reviews and user-generated content about the products have become one of the most crucial factors in determining whether to make a new purchase or otherwise, as e-commerce has grown substantially over the past years and has become increasingly important in our daily life, especially recently under the influence of COVID-19 (Hasanat et al., 2020). A survey conducted by Zhong-Gang et al., (2015) revealed that nearly 60% of consumers browse online product reviews at least once a week, and 93% of them believe that these online reviews help them improve the accuracy of purchase decisions. Therefore, this paper seeks to develop an AI model that calculates the product rating based on the likelihood of negative feedback in the written review and apply this model to a dataset downloaded from the Kaggle website (the dataset includes 23,486 records and 10 variables), customer reviews of women's clothing products, to compare the results from the model with the actual costumers' rates in the dataset. The premise of this paper is that reviews are more accurate than rates because reviews give consumers a chance to elaborate on their feedback and specifically point out the positive and negative aspects of a product. On the other hand, rates may be emotionally influenced by customers' feedback, as they may be very irate, which could affect how accurately they specify a value through rates. Consumers often have complaints about a particular aspect of a product, such as the packaging, the delivery date, or other issues that may not be related to the product itself as a commodity, nonetheless, they still rate the product very low, which is unfair and does not reflect the real evaluation of the product. In order to assist new clients in making better decisions, the outcome model developed in the paper should assist in providing a more precise, equitable, and reliable evaluation.
Eleraqi, A., & Elgenidy, S. (2023). AI Model to Calculate Products’ Rates Based on Customer's Reviews. The International Journal of Public Policies in Egypt (IJPPE), 2(2), 211-229. doi: 10.21608/ijppe.2023.296591
MLA
Amr Eleraqi; Sohaib Elgenidy. "AI Model to Calculate Products’ Rates Based on Customer's Reviews", The International Journal of Public Policies in Egypt (IJPPE), 2, 2, 2023, 211-229. doi: 10.21608/ijppe.2023.296591
HARVARD
Eleraqi, A., Elgenidy, S. (2023). 'AI Model to Calculate Products’ Rates Based on Customer's Reviews', The International Journal of Public Policies in Egypt (IJPPE), 2(2), pp. 211-229. doi: 10.21608/ijppe.2023.296591
VANCOUVER
Eleraqi, A., Elgenidy, S. AI Model to Calculate Products’ Rates Based on Customer's Reviews. The International Journal of Public Policies in Egypt (IJPPE), 2023; 2(2): 211-229. doi: 10.21608/ijppe.2023.296591
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