Published on: April 2026
EMOTION BEYOND WORDS: A MULTIDIMENSIONAL SENTIMENT INTELLIGENCE MODEL
A.Sathvika B. Udaya Sri P. Keerthi Sree GY. Shashank
Dr Pandi Chiranjeevi
Article Status
Available Documents
Abstract
How to Cite this Paper
A.Sathvika, , Sri, B. U., Sree, P. K. & Shashank, G. (2026). Emotion Beyond Words: A Multidimensional Sentiment Intelligence Model. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(04). https://doi.org/10.55041/ijcope.v2i4.164
A.Sathvika, , et al.. "Emotion Beyond Words: A Multidimensional Sentiment Intelligence Model." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i4.164.
A.Sathvika, ,B. Sri,P. Sree, and GY. Shashank. "Emotion Beyond Words: A Multidimensional Sentiment Intelligence Model." International Journal of Creative and Open Research in Engineering and Management 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i4.164.
References
- Zhao, K. Liu, and L. Xu, “Sentiment analysis: Mining opinions, sentiments, and emotions,” 2016.
- Medhat, A. Hassan, and H. Korashy, “Sentiment analysis algorithms and applications: A survey,” Ain Shams engineering journal, vol. 5, no. 4, pp. 1093 1113, 2014.
- Rad, C. Costache-Colareza, R.-V. Paraschiv, and L. Gavrila-Ardelean, “Synthetic emotions and the il lusion of measurement: A conceptual review and critique of measurement paradigms in affective sci ence,” Brain Sciences, vol. 15, no. 9, p. 909, 2025.
- Wang, Y. Wang, D. He, Z. Yu, Y. Li, L. Wang, J. Dang, and D. Jin, “Elevating knowledge-enhanced entity and relationship understanding for sarcasm de tection,” IEEE Transactions on Knowledge and Data Engineering, 2025.
- Kusal, S. Patil, J. Choudrie, K. Kotecha, D. Vora, and I. Pappas, “A systematic review of applications of natural language processing and future challenges with special emphasis in text-based emotion detec tion,” Artificial Intelligence Review, vol. 56, no. 12, pp. 15129–15215, 2023.
- T. Kokab, S. Asghar, and S. Naz, “Transformer based deep learning models for the sentiment analy sis of social media data,” Array, vol. 14, p. 100157, 2022.
- Cambria and A. Hussain, “Sentic computing: A common-sense-based framework for concept-level sentiment analysis; 2015; cham, switzerland.”
- Esmaeilzadeh, M. Heidari, R. Abdolazimi, P. Ha jibabaee, and M. Malekzadeh, “Efficient large scale nlp feature engineering with apache spark,” in 2022 IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC), pp. 0274–0280, IEEE, 2022
Ethical Compliance & Review Process
- •All submissions are screened under plagiarism detection.
- •Review follows editorial policy.
- •Authors retain copyright.
- •Peer Review Type: Double-Blind Peer Review
- •Published on: Apr 08 2026
This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. You are free to share and adapt this work for non-commercial purposes with proper attribution.

