International Journal of Information Engineering and Electronic Business (IJIEEB)
IJIEEB Vol. 17, No. 6, 8 Dec. 2025
Cover page and Table of Contents: PDF (size: 905KB)
Blockchain Framework for Sentiment Analysis from Unstructured Text Reviews
PDF (905KB), PP.34-47
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Author(s)
Pratik K. Agrawal
1,*
Monali Gulhane
1
Siddhi Kadu
2
Pravinkumar M. Sonsare
3
Index Terms
Blockchain, Deep Learning, Opinion Analysis, Machine Learning, Natural language Processing, Sentiment Analysis
Abstract
The E-commerce platform has provided the user and the organization with a new avenue for the product distribution and selling. The product distribution is greatly hampered by the opinions provided by the end user and if tampering and fake reviews are generated then it affects the product badly. The Natural language processing domain deals with the analysis of this review and provide the user with recommendation for decision making. The NLP domain deals with several issues like fake reviews, tampering with the reviews, and security for transfer of reviews etc. In this paper, a Blockchain based sentimental analysis module framework is proposed that provides the user with a secure and trustful environment for the opinions reviews as well as it provide a hybrid sentimental module that uses the algorithms from machine learning and deep learning for sentiment score generation. The Proposed Model was evaluated on different datasets of the varied domain. The proposed model performs a substantial improvement in providing the accurate results.
Cite This Paper
Pratik K. Agrawal, Monali Gulhane, Siddhi Kadu, Pravinkumar M. Sonsare, "Blockchain Framework for Sentiment Analysis from Unstructured Text Reviews", International Journal of Information Engineering and Electronic Business(IJIEEB), Vol.17, No.6, pp. 34-47, 2025. DOI:10.5815/ijieeb.2025.06.03
Reference
[1]Chen, Zhen-Song & Zhu, Zhengze & Wang, Zhu-Jun & Tsang, Y. P.. (2023). Fairness-aware large-scale collective opinion generation paradigm: A case study of evaluating blockchain adoption barriers in medical supply chain. Information Sciences. 635. 257–278. 10.1016/j.ins.2023.03.135.
[2]Bălă, Denisa & Stancu, Stelian. (2023). Using Twitter Data and Lexicon-Based Sentiment Analysis to Study the Attitude Towards Cryptocurrency Market and Blockchain Technology. 10.1007/978-981-19-6755-9_15.
[3]Wang, Zeyu & Zhang, Shuting & Zhao, Yuanyuan & Chen, Chuan & Dong, Xiufang. (2023). Risk prediction and credibility detection of network public opinion using blockchain technology. Technological Forecasting and Social Change. 187. 122177. 10.1016/j.techfore.2022.12217
[4]Hassani, Hossein & Razavi-Far, Roozbeh & Saif, Mehrdad & Herrera-Viedma, Enrique. (2023). Blockchain-Enabled Trust Building for Managing Consensus in Linguistic Opinion Dynamics. IEEE Transactions on Fuzzy Systems. 10.1109/TFUZZ.2023.3235411.
[5]Luo, Zhenqing & Zhang, Cheng. (2023). Applying Blockchain Technology in Network Public Opinion Risk Management System in Big Data Environment. Computational Intelligence and Neuroscience. 2023. 1-14. 10.1155/2023/5212712.
[6]Lade, Mitali & Welekar, Rashmi & Dadiyala, Charanjeet. (2023). Bitcoin Price Prediction and NFT Generator Based on Sentiment Analysis. International Journal of Next-Generation Computing. 10.47164/ijngc.v14i1.1043.
[7]Osman, Ismail & Husien, Idress. (2022). Comparison of Sentiment Analysis Techniques for Twitter posts classification. 93-97. 10.1109/ICDSIC56987.2022.10075895.
[8]Chen, Jie & Song, Nan & Su, Yansen & Zhao, Shu & Zhang, Yanping. (2022). Learning User Sentiment Orientation in Social Networks for Sentiment Analysis. Information Sciences. 616. 10.1016/j.ins.2022.10.135.
[9]Zhao, Zhihua & Hao, Zhihao & Wang, Guancheng & Mao, Dianhui & Zhang, Bob & Zuo, Min & Yen, Jerome & Tu, Guangjian. (2021). Sentiment Analysis of Review Data Using Blockchain and LSTM to Improve Regulation for a Sustainable Market. Journal of Theoretical and Applied Electronic Commerce Research. 17. 1-19. 10.3390/jtaer17010001.
[10]Verma, Pranjal & Ahuja, Tanushi & Yadav, Garima. (2021). A Blockchain-Based Sentiment Analysis Framework for Reliable Feedback System. 1-6. 10.1109/ICRITO51393.2021.9596356.
[11]Liang, Ye & Qin, Ying. (2020). Cross-Lingual Public Opinion Tracing Based on Blockchain Technology. 10.1007/978-3-030-60029-7_54.
[12]Q. Pan, X. Zheng and G. Chen, "A Mix-model based Deep Learning for Text Sentiment Analysis," 2018 International Conference on Cloud Computing, Big Data and Blockchain (ICCBB), Fuzhou, China, 2018, pp. 1-6, doi: 10.1109/ICCBB.2018.8756420.
[13]Kuo, Tsung-Ting & Kim, Hyeoneui & Ohno-Machado, Lucila. (2017). Blockchain distributed ledger technologies for biomedical and health care applications. Journal of the American Medical Informatics Association. 24. 1211-1220. 10.1093/jamia/ocx068.
[14]Yue, Xiao & Wang, Huiju & Jin, Dawei & Li, Mingqiang & Jiang, Wei. (2016). Healthcare Data Gateways: Found Healthcare Intelligence on Blockchain with Novel Privacy Risk Control. Journal of medical systems. 40. 218. 10.1007/s10916-016-0574-6.
[15]P. R. . Pardhi, J. K. . Rout, P. K. Agrawal, and N. K. . Ray, “Blockchain for decentralized malware detection on android devices”, J Integr Sci Technol, vol. 13, no. 4, p. 1084, Feb. 2025, doi: 10.62110/sciencein.jist.2025.v13.1084.
[16]Agrawal, P.K. A Novel Mapper Machine Learning Algorithm for Semantic Domain Mapping for Domain Database Updation. SN COMPUT. SCI. 4, 536 (2023). https://doi.org/10.1007/s42979-023-02036-0.
[17]Kadu, S., Joshi, B. & Agrawal, P. Optimization for Image Sentiment Analysis Using Novel Dual Moth Flame Algorithm. SN COMPUT. SCI. 6, 134 (2025). https://doi.org/10.1007/s42979-025-03670-6.