DEPARTMENT OF COMPUTER SCIENCES

This study examines how sentiment analysis shapes brand reputation management in a digital environment dominated by user-generated content and real-time public feedback. Using a mixed methods approach, the research integrates quantitative sentiment mining—via VADER and TextBlob—with qualitative interviews from brand managers and sentiment analysis experts. Quantitative data from social media and review platforms were analyzed to determine sentiment polarity and trends, while qualitative insights clarified how organizations interpret and apply these results. Findings show that sentiment analysis enhances reputation management by enabling real-time monitoring, early detection of emerging crises, and data-driven strategic decisions. Positive sentiment corresponds withstronger brand equity and loyalty, whereas negative sentiment, particularly on high-velocity platforms like Twitter, accelerates reputational risk. The study concludes that sentiment analysis is essential for proactive brand management and recommends broader adoption of AI-driven tools, improved crisis protocols, and continuous model updates to address linguistic nuances and reduce algorithmic bias.

This study critically analyzes the role of Clinical Decision Support Systems (CDSS) in enhancing healthcare delivery. Focusing on the period from 2020 onward, the research explores the applications and benefits of CDSS, including their potential to improve diagnostic accuracy and personalize treatment through precision medicine. The study also investigates the significant challenges hindering widespread CDSS adoption, such as technical barriers like interoperability issues with Electronic Health Records (EHRs), clinician resistance due to concerns about trust and workflow disruption, and ethical considerations surrounding data privacy, algorithmic bias, and accountability. Through a comprehensive review of existing literature and practices, the research aims to densify practical and innovative strategies for optimizing CDSS integration, usability, and acceptance in diverse healthcare settings, with a particular focus on the unique challenges faced by low-resource environments. The study's findings are intended to inform healthcare providers, policymakers, researchers, developers, and ultimately, patients, by providing insights into the potential and limitations of CDSS in improving healthcare delivery and patient outcomes.

This project focuses on the design and implementation of a web-based public complaint management system for the Benin Electricity Distribution Company (BEDC), aimed at addressing critical inefficiencies in traditional grievance handling processes. The system provides a structured digital platform that enables customers to submit, track, and monitor complaints related to power services, including outages, billing disputes, meter issues, and service delays, while allowing administrators to efficiently manage, process, and resolve grievances in a transparent and timely manner. Through a user-friendly web interface accessible via standard browsers, the platform eliminates challenges associated with manual complaint systems, such as lost records, delayed responses, lack of accountability, and poor tracking capabilities that have historically undermined customer trust and organizational credibility.
The study employs a systematic approach involving the investigation of existing manual and basic digital complaint management systems at BEDC, the identification of their limitations, and the development of an enhanced web-based solution using modern technologies, including HTML, CSS, JavaScript, PHP, and MySQL. Key features include secure user authentication, real-time complaint submission and tracking, automated workflows for efficient complaint routing, comprehensive database management for record-keeping, and administrative dashboards for monitoring and analyzing complaint patterns. The system incorporates robust security measures and accessibility features to accommodate diverse user groups while ensuring data privacy and integrity. By implementing this solution, the project addresses recurring issues such as delayed responses, limited transparency, and inadequate feedback
mechanisms that discourage customers from reporting grievances. The findings contribute to improved customer satisfaction, enhanced organizational efficiency through data-driven decision-making, and the advancement of knowledge on ICT applications in public utility administration, providing a scalable model for digital transformation in similar service sectors across Nigeria and beyond.