A Comprehensive Product Review System for Improved Customer Satisfaction

2023 2nd International Conference on Paradigm Shifts in Communications Embedded Systems, Machine Learning and Signal Processing (PCEMS) Pub Date : 2023-04-05 DOI:10.1109/PCEMS58491.2023.10136118

Anamika Bisane, Shivanand Chandravanshi, P. Thakre, Purab Kesharwani, Atiya Khan

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Abstract

Digital reviews now have a significant impact on how consumers communicate globally and how they make purchases. When a buyer looks at the product’s ratings and reviews, they are frequently confused by the sheer volume of them. In the proposed study, product reviews are classified into positive and negative sentiments using the VADER (Valence Aware Dictionary for Sentiment Reasoning), a machine learning model that classifies reviews into positive and negative sentiments based on attributes discovered by the model that is used in the proposed work to categories product reviews into positive and negative categories. We provide the consumer with a graph of the number of good and negative reviews for the product they are interested in, as well as the total positive and negative review polarity for the item. To save clients’ time, a graphical representation of the analysis is also given.

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一个全面的产品审查系统，以提高客户满意度

如今，数字评论对全球消费者的沟通方式和购买方式产生了重大影响。当买家看到产品的评级和评论时，他们经常会被大量的评级和评论所迷惑。在提出的研究中，使用VADER(情感推理的价觉字典)将产品评论分类为积极和消极情绪，这是一种机器学习模型，该模型根据模型发现的属性将评论分类为积极和消极情绪，该模型用于将产品评论分类为积极和消极类别。我们向消费者提供他们感兴趣的产品的好评和差评数量的图表，以及该产品的总好评和差评极性。为了节省客户的时间，还给出了分析的图形表示。

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2023 2nd International Conference on Paradigm Shifts in Communications Embedded Systems, Machine Learning and Signal Processing (PCEMS)

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