Sentiment Analysis using Latent Dirichlet Allocation for Aspect Term Extraction


  • Lovish Rajput Department of Information Technology, JSS Academy of Technical Education, Noida, Uttar Pradesh, India 201301
  • Shilpi Gupta Department of Information Technology, JSS Academy of Technical Education, Noida, Uttar Pradesh, India 201301



Sentiment analysis, Latent Dirichlet Allocation (LDA), Product design, User-generated text data, Opinion mining


This work proposes a sentiment analysis approach for decision-making in product design, analysis, and market share. The approach incorporates user-generated text data in the form of consumer reviews to extract product features using topic-based modeling methods. Latent Dirichlet Allocation (LDA) is employed to extract aspect categories from the data and identify the sentiment of each review using the VADER sentiment analyzer. The performance of the proposed method is evaluated in terms of accuracy, with an achieved result of 80%. The extracted topics are also summarized to provide leads for product design and quality assurance. The approach can be used by manufacturers, retailers, and suppliers to understand customers' opinions about their products better and make better decisions. LDA is a powerful unsupervised method that can extract latent topics from a collection of documents; this method has been widely used in text mining, information retrieval, and natural language processing. The accuracy can be improved by using more sophisticated models or more data.

Author Biography

Shilpi Gupta, Department of Information Technology, JSS Academy of Technical Education, Noida, Uttar Pradesh, India 201301

Ms. Shilpi Gupta is an Assistant Professor in the Department of Information Technology at JSS Academy of Technical Education, with 13 years of teaching experience. She holds a B.E. in Computer Science & Engineering from BBIT, Ghaziabad, UPTU, Lucknow, and an M.Tech in Computer Science & Engineering from PDM, Bahadurgarh MDU, Rohtak. She is currently pursuing a Ph.D. in Computer Science from Shobhit Institute of Engineering & Technology, Meerut, Shobhit Deemed University. Ms. Gupta has authored a book chapter on Natural Language Processing in Online Reviews, which appears in the book Natural Language Processing for Global and Local Business published by IGI Global in 2021. She has also received a patent for her work on a Depression Detection Device using Multichannel Electroencephalography, which was published on 30/12/2022.



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How to Cite

Rajput, L., & Gupta, S. (2022). Sentiment Analysis using Latent Dirichlet Allocation for Aspect Term Extraction. Journal of Computers, Mechanical and Management, 1(2), 30–35.



Research Articles