JOURNAL ARTICLE

Sentiment Analysis Using Naïve Bayes Algorithm: With Case Study

Abstract

Data is the new oil. It becomes valuable only when mined appropriately. Huge amounts of money is invested in the Data segment in the company only because the companies know its importance. Apart from profit generating information, the companies also need to know the customers' opinions of about the measures implemented. Text mining is the discovery of valuable information from the text in a text file. Online Text mining relates to gathering the information from social media posts such as tweets and blogs. Sentiment Analysis is the computational treatment of opinion, sentiment and subjectivity [4]. Sentiment Analysis of this information extends to the emotions behind this information which assists in selecting appropriate steps. In this paper we chose to mine the opinion of people regarding the two most important measures taken by the Government of India - Demonetization and Goods and Services Tax (GST).

Keywords:
Sentiment analysis Naive Bayes classifier Computer science Social media Profit (economics) Government (linguistics) Data science Information retrieval World Wide Web Artificial intelligence Support vector machine

Metrics

4
Cited By
0.40
FWCI (Field Weighted Citation Impact)
9
Refs
0.71
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Text and Document Classification Technologies
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Text Analysis Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Bayesian Modeling and Causal Inference
Physical Sciences →  Computer Science →  Artificial Intelligence

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