Advancements in sentiment analysis – A comprehensive review of recent techniques and challenges
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2025.16.spl-1.09Keywords:
Sentiment analysis, Machine learning, Deep learning, Aspect analysis, Emotion Detection, Fine-grained Sentiment analysisDimensions Badge
Issue
Section
License
Copyright (c) 2025 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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.Abstract
How to Cite
Downloads
Similar Articles
- Deo Narayan, C. D. Agashe, K. D. Verma, Impact of Different Individual Games on Selected Personality Traits , The Scientific Temper: Vol. 12 No. 1&2 (2021): The Scientific Temper
- Teklil Abadeye, Teshome Yitbarek, Isreal Zewide, Kibinesh Adimasu, Assessing soil fertility influenced by land use in Moche, Gurage Zone, Ethiopia , The Scientific Temper: Vol. 14 No. 01 (2023): The Scientific Temper
- Vandana, Ambrish Pandey, Comparative analysis of print contrast of hybrid modulated digitally modulated screening on different grades of paper , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Nilesh M. Patil, P M. Krishna, G. Deena, C Harini, R.K. Gnanamurthy, Romala V. Srinivas, Exploring real-time patient monitoring and data analytics with IoT-based smart healthcare monitoring , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Siddharth P. Singh, Amar B. Verma, Ankur Srivastava, Kamlesh K. Chaurasiya, Anil Kumar, Prashant K. Singh, Sindhu Singh, Design Design, structural, and electrical conduction behavior of Zr-modified BaTiO3-BiFeO3 perovskite ceramics , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Archana Verma, Role of artificial intelligence in evaluating autism spectrum disorder , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- U. Perachiselvi, R. Balasubramani, Funding agencies in Tamil Nadu State Universities: A scientometric perspective , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- J. Pavithra, Status of investment in startup in India – An analysis , The Scientific Temper: Vol. 16 No. Spl-2 (2025): The Scientific Temper
- Priyanka Prajapati, Dipak Makwana, Work-Life Balance, Mental Health, and Sustainable Innovation: A Study of Women in Industry , The Scientific Temper: Vol. 17 No. 03 (2026): The Scientific Temper
- MRINAL CHANDRA, DEVELOPMENT OF METHOD FOREXTRACTIVE SPECTROPHOTOMETRIC DETERMINATION OF COPPER(II) WITH N-BENZOYL THIOUREATHIOSEMICARBONZONE(MAAPHE) AS AN ANALYTICAL REAGENT , The Scientific Temper: Vol. 8 No. 1&2 (2017): The Scientific Temper
<< < 42 43 44 45 46 47 48 49 50 51 > >>
You may also start an advanced similarity search for this article.

