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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Islabudeen Mohamed Meerasha
Presidency University
Computer Science & IT Engineering

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A comprehensive analysis of consumer decisions on Twitter dataset using machine learning algorithms Vigneshwaran Pandi; Prasath Nithiyanandam; Sindhuja Manickavasagam; Islabudeen Mohamed Meerasha; Ragaventhiran Jaganathan; Muthu Kumar Balasubramanian
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i3.pp1085-1093

Abstract

An exponential growth posting on the web about the product reviews on social media, there has been a great deal of examination being done on sorting out the purchasing behaviors of the client. This paper depends on utilizing twitter for sentiment analysis to comprehend the customer purchasing behavior. There has been a significant increase in e-commerce, particularly in persons purchasing products on the internet. As a result, it becomes a fertile hotspot for opinion analysis and belief mining. In this investigation, we look at the problem of recognizing and anticipating a client's purchase goal for an item. The sentiment analysis helps to arrive at a more indisputable outcome. In this study, the support vector machine, naive Bayes, and logistic regression methods are investigated for understanding the customer's sentiment or opinion on a specific product. These strategies have been demonstrated to be genuinely for making predictions using the analysis models which examine the client's conclusion/sentiment the most precisely. The exactness for each machine learning algorithm will be analyzed and the calculation which is the most precise would be viewed as ideal.
Co-Authors Muthu Kumar Balasubramanian Prasath Nithiyanandam Ragaventhiran Jaganathan Sindhuja Manickavasagam Vigneshwaran Pandi