This study investigates the integration of sentiment analysis with machine learning models to forecast stock price movements using the Nvidia Corporation as a case study. Sentiment scores were derived from Nvidia-related financial news headlines using two sentiment analysis tools: FinBERT, a...

The health sector requires skilled, altruistic, and motivated individuals to perform complex tasks for which ex-post incentives may prove ineffective. Understanding the determinants of self-selection into health professions is therefore critical. We investigate this issue relying on data from...

Efficient identification of critical links in urban road networks is essential for optimizing traffic management, infrastructure planning, and resource allocation. Existing methods, such as simulation-based approaches, are computationally expensive and often impractical for large-scale networks....

Employee turnover poses a significant challenge to organizations, leading to increased costs and disruptions in workforce stability. In this study, we propose a novel hybrid model for employee turnover prediction that integrates Genetic Algorithms (GA) for feature selection with LightGBM for...

Industry 4.0 technologies have provided industries and firms with enormous capacities for data exchange, especially shopfloor sectors. This digitized data exchange process is accumulated exponentially and is necessitating mechanisms for adding value to the business firms. This paper has focused...