Aspect based sentimental analysis on e-commerce review
Sudhakar Pal
, Pankaj Yadav , Dr. Santosh Kumar Singh , Sherilyn kevin
Sentiment Analysis, E-Commerce, Natural Language Processing (NLP), VADER, RoBERTa, Opinion Mining.
The digital marketplace is fueled by customer feedback, with e-commerce platforms generating a vast and constant stream of user reviews. Understanding the sentiments within this text is crucial for businesses, yet manually processing such large volumes of data is impractical. This research explores automated sentiment analysis by comparing two distinct methodological approaches applied to a dataset of e-commerce reviews. We evaluate the performance of VADER, a lexicon and rule-based model, against RoBERTa, a state-of-the-art transformer model. Our findings demonstrate that advanced deep learning techniques like RoBERTa achieve higher accuracy than traditional methods, offering a more nuanced understanding of customer opinions. The study underscores the value of sophisticated sentiment analysis as a powerful tool for data-driven decision-making in the e-commerce sector.
"Aspect based sentimental analysis on e-commerce review", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.10, Issue 9, page no.b442-b449, September-2025, Available :https://ijsdr.org/papers/IJSDR2509154.pdf
Volume 10
Issue 9,
September-2025
Pages : b442-b449
Paper Reg. ID: IJSDR_305034
Published Paper Id: IJSDR2509154
Downloads: 00042
Research Area: Science All
Country: Mumbai, Maharstra, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
