Authors:
Vatsala Sharma, Krishna Kant Agrawa, Harikesh Singh, Pramod Kumar Sagar, Rajesh Kumar Maurya, Dimitrios A. Karras

Addresses:
Department of Electronics and Communication Engineering, Government Engineering College, Buxar, Bihar, India. School of Computer Science and Engineering, Galgotias University, Gautam Buddh Nagar, Uttar Pradesh, India. Department of Computer Science and Engineering (Data Science), GL Bajaj Institute of Technology and Management, Gautam Buddh Nagar, Uttar Pradesh, India. Department of Computer Science and Engineering, Raj Kumar Goel Institute of Technology, Ghaziabad, Uttar Pradesh, India. Department of Computer Applications, ABES Engineering College, Ghaziabad, Uttar Pradesh, India. Department of Computer Engineering, EPOKA University, Tiranë-Rinas, Tirana, Albania.

Abstract:

AI technology is transforming our progress and the management of complex systems. Human behavior and sentiment analysis, which heavily drive decision-making and risk evaluation, are among the Fundamental Challenges of Optimising Complex Systems. With seemingly endless growth in data volume and recent advancements in deep learning, there is growing interest in integrating higher-level cognitive frameworks into complex systems to develop a deeper understanding and address the aforementioned challenges. In this work, researchers present a cognitive-focused deep learning-based abstraction for human perception and mood-motivated risk modeling of complex systems. The proposed model obtained 82.23% risk assessment, 78.28% scalability, 83.24% robustness, and 79.22% Interpretability. Alongside cognitive models, this deep learning framework is presented as a framework based on multiple natural language processing techniques, while also offering insight into the human context and sentiment regarding a specific complex system, based on data extracted from multiple sources. This will involve extracting data from social media, news stories, and other sources to gauge public mood and stakeholders' views on the system, as well as analyzing internal data from the system.

Keywords: Human Perception; Sentiment Analysis; Decision Making; Risk Assessment; News Analysis; Data Extraction; Stakeholder Sentiment; Human Context; Complex Systems.

Received on: 13/02/2025, Revised on: 10/04/2025, Accepted on: 15/07/2025, Published on: 11/01/2026

DOI: 10.69888/FTSCS.2026.000607

FMDB Transactions on Sustainable Computing Systems, 2026 Vol. 4 No. 1, Pages: 22-34

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