Consumer Approach to AI Driven Sentiment Analyzer: A Literature Review

Kavya P; Ananya M Hegde; Akanksha Giliyal; Geethika S; Dr. Pooja Nayak S

Consumer Approach to AI Driven Sentiment Analyzer: A Literature Review

February 2023

Vol-9, Issue-1

Paper ID: 19155

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Computer Science Engineering

Keywords

sentiment-analysis consumer classification machine learning KNN Naive Bayes SVM.

Abstract

Customers are valued by a business not just for their financial impact, but also for how satisfied they are with the service they receive and it is subjective. Positive word-of-mouth is disseminated by satisfied consumers, and negative word-of-mouth by disappointed ones. Due to subjectivity, it is vital to examine a variety of perspectives rather than just one that conveys one person’s subjective viewpoint. In addition to the abundance of sources, the volume of data makes it impossible to manually sort through them to find the underlying trends, issues, or reasons of (dis)satisfaction. Sentiment analysis is a potent tool that enables users to both extract the necessary data and aggregate the overall sentiments of the reviews. For completing this goal, a number of strategies have gained attention in recent years. This paper examines the various Sentiment Analysis strategies of machine learning such as K-NN classifier, Naive Bayes classifier, Support Vector Machine (SVM), and Neural Networks.

License

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Author Information

#	Name	Institute / Affiliation
1	Kavya P	Dayananda Sagar Academy of Technology and Management
2	Ananya M Hegde	Dayananda Sagar Academy of Technology and Management
3	Akanksha Giliyal	Dayananda Sagar Academy of Technology and Management
4	Geethika S	Dayananda Sagar Academy of Technology and Management
5	Dr. Pooja Nayak S	Dayananda Sagar Academy of Technology and Management

How to Cite

Use the following formats to cite this article in your research.

APA Style

P, Kavya, Hegde, Ananya M, Giliyal, Akanksha, S, Geethika, & S, Dr. Pooja Nayak (2023). Consumer Approach to AI Driven Sentiment Analyzer: A Literature Review. International Journal of Advance Research and Innovative Ideas In Education, 9(1), 1225-1231.

MLA Style

P, Kavya, et al. "Consumer Approach to AI Driven Sentiment Analyzer: A Literature Review." International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 1, 2023, pp. 1225-1231.

IEEE Style

Kavya P, Ananya M Hegde, Akanksha Giliyal, Geethika S, and Dr. Pooja Nayak S, "Consumer Approach to AI Driven Sentiment Analyzer: A Literature Review," International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 1, pp. 1225-1231, 2023.

Vancouver Style

P Kavya, Hegde Ananya M, Giliyal Akanksha, S Geethika, S Dr. Pooja Nayak. Consumer Approach to AI Driven Sentiment Analyzer: A Literature Review. International Journal of Advance Research and Innovative Ideas In Education. 2023;9(1):1225-1231.

Harvard Style

P, Kavya, Hegde, Ananya M, Giliyal, Akanksha, S, Geethika, & S, Dr. Pooja Nayak (2023) 'Consumer Approach to AI Driven Sentiment Analyzer: A Literature Review', International Journal of Advance Research and Innovative Ideas In Education, 9(1), pp. 1225-1231.

Chicago Style

P, Kavya, et al. "Consumer Approach to AI Driven Sentiment Analyzer: A Literature Review." International Journal of Advance Research and Innovative Ideas In Education 9, no. 1 (2023): 1225-1231.

Turabian Style

P, Kavya, et al. "Consumer Approach to AI Driven Sentiment Analyzer: A Literature Review." International Journal of Advance Research and Innovative Ideas In Education 9, no. 1 (2023): 1225-1231.