ICICBDA-Framework-for-Sentiment-Analysis

An Intelligent Cognitive-Inspired Computing with Big Data Analytics Framework for Sentiment Analysis and Classification

---

📖 Project Information

Authors:
Prasanthi Boyapati, Deepak Kumar Jain, J. Venkatesh, M. Prakash

Published In:
Elsevier, Information Processing & Management, Volume 59, Issue 1, January 2022

DOI:
10.1016/j.ipm.2021.102758

Impact:
Q1 Journal, SCI Indexed, Highly Cited Article

---

🧠 Abstract

This project introduces a cognitive-inspired computing framework combined with Big Data Analytics to efficiently tackle Sentiment Analysis (SA) and Classification tasks. Leveraging Hadoop MapReduce for scalable processing and an innovative BBSO-FCM hybrid model, the framework significantly enhances sentiment prediction, making it ideal for real-world, large-scale datasets.

---

🚀 Key Contributions

• Cognitive-Inspired Model:
  Integration of Binary Brain Storm Optimization (BBSO) with Fuzzy Cognitive Maps (FCMs).

• Big Data Compatibility:
  Utilizes Hadoop MapReduce for large dataset processing.

• Superior Performance:
  Achieved 96% classification accuracy, outperforming state-of-the-art models.

• Social Impact:
  Supports healthcare, governance, and e-commerce industries by enabling real-time, scalable sentiment monitoring.

• Efficiency:
  Reduces computational complexity via optimal feature selection.

---

🌍 Real-World Relevance

• Business Intelligence: Monitor brand reputation and public opinion in real time.
• Healthcare: Detect early warning signs in public mental health trends.
• Governance: Analyze public feedback to inform policy-making.
• Scientific Advancement: Advances cognitive computing integration in Big Data contexts.

---

📊 Experimental Results Summary

Metric	Proposed BBSO-FCM	Gradient Boosted SVM	Random Forest	SVM	Logistic Regression
Accuracy (TF-IDF)	96%	93%	87%	91%	88%
Precision	0.97	0.92	0.89	0.91	0.88
Recall	0.89	0.84	0.71	0.83	0.75
F1 Score	0.92	0.88	0.78	0.86	0.82

Highlights:
The BBSO-FCM model demonstrated remarkable improvements in Accuracy, Precision, Recall, and F1-score.

---

📚 Citation

@article{JainBoyapati2022,
  title={An Intelligent Cognitive-Inspired Computing with Big Data Analytics Framework for Sentiment Analysis and Classification},
  author={Deepak Kumar Jain, Prasanthi Boyapati, J. Venkatesh, M. Prakash},
  journal={Information Processing & Management},
  volume={59},
  number={1},
  year={2022},
  doi={10.1016/j.ipm.2021.102758}
}

---

📜 License

This project is released for academic and non-commercial use only.
For commercial licensing inquiries, please contact the corresponding authors.

---

🔗 Resources

• 🔗 Full Paper on ScienceDirect
• 📚 Information Processing and Management Journal

---

👩‍💻 Author Contact

• Prasanthi Boyapati — bprasanthi@rvrjc.ac.in
• Deepak Kumar Jain — deepak@cqupt.edu.cn

---

🏆 Societal Impact

This framework empowers enterprises, governments, and communities to make smarter, data-driven decisions by deeply understanding public sentiment at scale — fostering safer, healthier, and more responsive societies.

---

Thank you for visiting this project! Feel free to explore, cite, and connect! 🚀