Advancements in sentiment analysis – A comprehensive review of recent techniques and challenges

Published

21-05-2025

DOI:

https://doi.org/10.58414/SCIENTIFICTEMPER.2025.16.spl-1.09

Keywords:

Sentiment analysis, Machine learning, Deep learning, Aspect analysis, Emotion Detection, Fine-grained Sentiment analysis

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Authors

  • Mansi Harjivan Chauhan Computer Engineering, Atmiya University, Rajkot, India.
  • Divyang D. Vyas Electronics & Communication Engineering, Atmiya University, Rajkot, India.

Abstract

In an increasingly digital world, opinions and emotions expressed across a variety of online platforms, when analyzed,propose immense potential for businesses, governments, and organizations. Sentiment analysis includes a collection of techniques that provide a fast and efficient way to classify user comments and derive meaningful information. Though sentiment analysis has been in practice for quite some time, there is a significant advancement in terms of approaches used because of increasing amounts of available data in various forms, including text, requirement of contextual understanding, business needs, etc. This article provides a comprehensive review of the latest advancements in sentiment classification in terms of scope, techniques and challenges. This literature review presents a good insight into the classification of various approaches in sentiment analysis and comparative analysis of different techniques. It also highlights the challenges in terms of the research gap and proposes future directions.

How to Cite

Chauhan, M. H., & Vyas, D. D. (2025). Advancements in sentiment analysis – A comprehensive review of recent techniques and challenges. The Scientific Temper, 16(Spl-1), 63–69. https://doi.org/10.58414/SCIENTIFICTEMPER.2025.16.spl-1.09

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