JOURNAL ARTICLE

Sentiment Analysis of Snack Review Using the Naïve Bayes Method

Abstract

Fast food is a product that we often encounter in stores such as convenience stores. Ready-to-eat products can now be easily found by consumers. One of the reason is due to the expansion of minimarkets in areas that are easily reached, such as housing complexes, school areas, and offices. Sentiment analysis is used to determine whether an opinion or comment on a product has a positive or negative interest and can be used as a reference in improving service, or improving product quality. In this research, we study the sentiments of consumers towards snack food products as a reference to improve the level of service and quality of these products.. We classify the sentiment of a review on snack food products as positive and negative. To classify the sentiments we apply the Naïve Bayes and Multinomial Naïve Bayes methods. We compare the two methods to study the most effective and efficient method for classifying sentiments on reviews of snack food products. Keywords: Sentiment Analysis, TF-IDF, Naïve Bayes,Multinomial, Review, Snack, Preprocessing

Keywords:
Product (mathematics) Naive Bayes classifier Sentiment analysis Quality (philosophy) Multinomial distribution Bayes' theorem Snack food Food products Computer science Service (business) Preprocessor Bayesian probability Advertising Marketing Statistics Artificial intelligence Business Food science Mathematics

Metrics

2
Cited By
0.15
FWCI (Field Weighted Citation Impact)
2
Refs
0.59
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Sentiment Analysis and Opinion Mining
Physical Sciences →  Computer Science →  Artificial Intelligence
Information Retrieval and Data Mining
Physical Sciences →  Computer Science →  Information Systems
Advanced Text Analysis Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
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