This paper presents an innovative approach to stock market prediction by extending the analysis beyond traditional financial indicators. In addition to exploring the influence of HR management metrics on stock values, we introduce a novel dimension— incorporating sentiment analysis from social media platforms. The study comprehensively examines various deep learning algorithms to predict stock values, considering the dynamic nature of public perception and sentiment expressed online. By integrating HR management practices and social sentiment into our models, we aim to provide a holistic understanding of factors influencing stock market dynamics. This research not only expands the horizons of predictive analytics in finance but also opens avenues for exploring unconventional connections between corporate practices, public sentiment, and market performance.