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Sentiment analysis versus aspect-based sentiment analysis versus emotion analysis from text: a comparative study

Author

Listed:
  • Diksha Shukla

    (Babasaheb Bhimrao Ambedkar University (A Central University))

  • Sanjay K. Dwivedi

    (Babasaheb Bhimrao Ambedkar University (A Central University))

Abstract

In recent years, due to the rapid expansion of Web 2.0 and the evaluation of the internet era, text-based communication over social networking sites is effectively used for sharing emotions or feelings with the entire world. People are using social media networks such as YouTube, Instagram, Facebook, & Twitter to express their feelings, opinions, arguments, and emotions about any organization, services, products, people, and so on. Every second large amount of unstructured contents are produced by these online communities and hence data can be analyzed or processed to understand human behavior and it can be done using sentiment analysis (SA). In some applications sentiment analysis is insufficient because it assesses only the positive or negative attitude; hence we require more advanced analysis techniques namely Emotion analysis (EA) and Aspect-based sentiment analysis (ABSA). This paper explores the differences between traditional SA, EA, and ABSA, the pipeline of SA, ABSA, and EA from text, issues in the area of SA, ABSA, and EA from text, and finally, discusses the Datasets used and their challenges.

Suggested Citation

  • Diksha Shukla & Sanjay K. Dwivedi, 2025. "Sentiment analysis versus aspect-based sentiment analysis versus emotion analysis from text: a comparative study," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 16(2), pages 512-531, February.
  • Handle: RePEc:spr:ijsaem:v:16:y:2025:i:2:d:10.1007_s13198-024-02666-4
    DOI: 10.1007/s13198-024-02666-4
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    References listed on IDEAS

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    1. Alim Al Ayub Ahmed & Sugandha Agarwal & IMade Gede Ariestova Kurniawan & Samuel P. D. Anantadjaya & Chitra Krishnan, 2022. "Business boosting through sentiment analysis using Artificial Intelligence approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 699-709, March.
    2. B. Vamshi Krishna & Ajeet Kumar Pandey & A. P. Siva Kumar, 2021. "Universally domain adaptive algorithm for sentiment classification using transfer learning approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(3), pages 542-552, June.
    3. Lina Sun & Rajiv Kumar Gupta & Amit Sharma, 2022. "Review and potential for artificial intelligence in healthcare," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 54-62, March.
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