DESIGNING AND IMPLEMENTING A MULTI-CRITERIA INTELLIGENT FRAMEWORK TO ENSURE THE RELEVANCE OF REQUIREMENTS SOURCED FROM SOCIAL NETWORK SITES

The proliferation of social networking sites (SNS) and software failures primarily arising from the requirements elicitation phase, motivated researchers to develop methods, that incorporate SNS-based users’ needs into the requirements engineering stage, crucial for developing reliable software. This approach improves user-centric needs and identifies innovative features, but relevance verification has not been thoroughly examined, leading to challenges in filtering and prioritizing relevant information emanated from jargon, informal language, and diverse expressions detected in user comments. This research proposes a novel intelligent framework for relevance verification of SNS-sourced requirements, combining multiple criteria like organizational goals, business rules, related service datasets, and user comments. The proposed framework balances user, organization, and developer needs by simplifying the process of determining relevant requirements and enhancing their validity. The framework learns and utilizes consolidated criteria features as regulation mechanisms, addressing challenges in isolating relevant users' needs and minimizing traditional method limitations. The study uses qualitative methods for framework development and empirical research methods for sentiment and trend analysis, combining customized word embedding models and natural language processing. A case study of digital healthcare systems in developing nations explores three evaluation categories: business rules, related service datasets, and a blend of both. The dataset includes 2400 key phrases from 800 user needs, 540 business goals, and 900 from service datasets. The proposed method achieved a relevance rate of 88%, surpassing individual methods. The study contributes to IT and software engineering fields by providing a novel framework for relevance verification of SNS-based requirements, ensuring their alignment with actual user needs and improving their completeness and prioritization, leading to significant enhancements in system design and development.