Food Review Analysis and Sentiment Prediction using Machine Learning Models

被引：2

作者：

Gupta, Dhruv ^{[1
]}

Roup, Ausho ^{[1
]}

Gupta, Diksha ^{[1
]}

Ratre, Avinash ^{[1
]}

机构：

[1] Delhi Technol Univ, Elect & Commun Engn Dept, Delhi, India

来源：

2022 SECOND INTERNATIONAL CONFERENCE ON ADVANCES IN ELECTRICAL, COMPUTING, COMMUNICATION AND SUSTAINABLE TECHNOLOGIES (ICAECT) | 2022年

关键词：

review analysis; sentiment analysis; data mining; natural language processing; machine learning;

D O I：

10.1109/ICAECT54875.2022.9807907

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this era of the digital world, text, messages, comments, numbers and videos have become an essential source of information. The trend of people trading through ecommerce giants like Amazon and Flipkart is proliferating. It's necessary to have a model or tool that helps retrieve helpful information from the customers' online reviews quickly that can also help product manufacturers have a better idea of their product. This paper targets the food industry, and a model is proposed that analyzes the customer reviews based on NLP techniques- TF-IDF Vectorizer and Count Vectorizer. Based on these analyses, customer sentiments are predicted using different machine learning classification algorithms like Logistic regression, Dummy classifier and Random forest classifier.

引用

页数：7

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