Analyzing sentiments in e-commerce: Techniques, applications and challenges

Sentiment Analysis (SA), a crucial component of Natural Language Processing (NLP), involves discerning sentiment within textual data. While widely applicable across diverse domains, this paper specifically focuses on SA within E-Commerce datasets. Serving as a concise review for beginners, the paper encompasses an overview of approximately twenty early works in SA. It elucidates the techniques employed, SA levels, and delineates the methodologies underpinning these approaches. In addition to elucidating the foundational methodologies, this paper provides insights into the applications of SA. It sheds light on how SA techniques find practical utility in discerning and interpreting sentiment nuances within the realm of E-Commerce. Furthermore, the paper delves into the challenges intrinsic to SA, offering a comprehensive understanding of the intricacies associated with this NLP task.

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Publication Details

Journal
International Journal of Science and Research Archive
Published
2024-08-23
DOI
https://doi.org/10.30574/ijsra.2024.12.2.0843
Primary Topic
Sentiment Analysis and Opinion Mining
Type
article
Field-Weighted Citation Impact
0.00
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article

Analyzing sentiments in e-commerce: Techniques, applications and challenges

Amrithkala M. Shetty, Manjaiah D.H
International Journal of Science and Research Archive
Sentiment Analysis and Opinion Mining
article

Analyzing sentiments in e-commerce: Techniques, applications and challenges

Amrithkala M. Shetty, Manjaiah D.H
article en

Abstract

Sentiment Analysis (SA), a crucial component of Natural Language Processing (NLP), involves discerning sentiment within textual data. While widely applicable across diverse domains, this paper specifically focuses on SA within E-Commerce datasets. Serving as a concise review for beginners, the paper encompasses an overview of approximately twenty early works in SA. It elucidates the techniques employed, SA levels, and delineates the methodologies underpinning these approaches. In addition to elucidating the foundational methodologies, this paper provides insights into the applications of SA. It sheds light on how SA techniques find practical utility in discerning and interpreting sentiment nuances within the realm of E-Commerce. Furthermore, the paper delves into the challenges intrinsic to SA, offering a comprehensive understanding of the intricacies associated with this NLP task.

International Journal of Science and Research ArchiveVol. 12(2)
Mangalore University (IN)
Quality Education
Openalex Percentile: Top 88%
Sentiment Analysis and Opinion Mining
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