Natural Language Processing for Sentiment Analysis Techniques and Applications

被引：0

作者：

Subbamma, T. Venkata ^{[1
]}

Mantravadi, Nagesh ^{[2
]}

Shalom, Angel Ruth ^{[3
]}

Tajne, Niket ^{[4
]}

Sreenivasulu, Gopu ^{[5
]}

Goud, Veer Sudheer ^{[6
]}

机构：

[1] Anurag Univ, Dept CSE DS, Hyderabad, India

[2] Koneru Lakshmaiah Educ Fdn, Dept ECE, Vaddeswaram, India

[3] Mangalayatan Univ Jabalpur, Fac Humanities, Dept English, Richhai, India

[4] Symbiosis Sch Online & Digital Learning, SIU Knowledge Village, Pune, India

[5] Rajeev Gandhi Mem Coll Engn & Technol Autonomous, Dept Civil Engn, Nandyala, India

[6] St Martins Engn Coll, Dept AI & DS, Secunderabad, India

来源：

METALLURGICAL & MATERIALS ENGINEERING | 2025年 / 31卷 / 03期

关键词：

Natural Language Processing; Sentiment Analysis; Machine Learning; Deep Learning; Transformer Models; Text Classification; Opinion Mining;

D O I：

暂无

中图分类号：

TF [冶金工业];

学科分类号：

0806 ;

摘要：

Sentiment analysis expert systems have gained intensive market attention because of the vast increase in customer-generated online feedback through reviews and social media posts and feedback. The study examines basic methods of sentiment analysis which consist of lexiconbased approaches as well as machine learning and deep learning systems. The paper evaluates practical uses of sentiment analysis along with discussing current field obstacles and prospective research paths for the upcoming years. New NLP technology particularly using transformer models improves sentiment analysis systems while enhancing their precision and speed.

引用

页码：194 / 200

页数：7

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