Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/497168
Title: Design and Development of Hybrid NLP Model for Sentiment Analysis of Social Media Data
Researcher: Santoshi Kumari
Guide(s): Pushphavathi, T P
Keywords: Computer Science
Computer Science Interdisciplinary Applications
Engineering and Technology
University: M S Ramaiah University of Applied Sciences
Completed Date: 2023
Abstract: Sentiment analysis is referred as a opinion mining process in natural language processing method, To newlineexamine whether the data is negative, positive or neutral. To help business, sentimental analysis acts on newlinetextual data by monitoring product sentiment in customer feedback. Towards an opinion target Aspect newlinelevel sentimental classification determine the sentiment polarity of a review sentence. A Sentence newlineconsists of various sentiment target pairs, in this task the challenge is to part different opinion for newlinedifferent target. The ABSA is widely utilized in monitoring social media, management of customer newlinesupport, analysis of the product, researching the competitive market, and so on. Several methods are newlinedevised using neural networks for the ABSA for the above-mentioned application domains, still, the newlineaccuracy of detection is a difficult task, which motivates to development of an ABSA by reviewing the newlinerelated literature to fulfill the drawback with a novel technique.
Pagination: IX,108
URI: http://hdl.handle.net/10603/497168
Appears in Departments:Department of Computer Science and Engineering

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02_preliminary pages.pdf473.96 kBAdobe PDFView/Open
03_chapter 1.pdf486.39 kBAdobe PDFView/Open
04_chapter 2.pdf824.82 kBAdobe PDFView/Open
05_chapter 3.pdf1.33 MBAdobe PDFView/Open
06_chapter 4.pdf1.5 MBAdobe PDFView/Open
07_chapter 5.pdf594.23 kBAdobe PDFView/Open
08_references.pdf564.75 kBAdobe PDFView/Open
80_recommendation.pdf585.45 kBAdobe PDFView/Open
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