Leveraging the capabilities of MapReduce and Big Data frameworks, real-time analysis is performed on extensive datasets extracted from social media platforms, like Twitter, and news outlets
Nikitha Sri Garapati (Northwest Missouri State University), Sri Sowmya Polampalli (Northwest Missouri State University), Isam Alobaidi (Northwest Missouri State University)
Leveraging the capabilities of MapReduce and Big Data frameworks, real-time analysis is performed on extensive datasets extracted from social media platforms, like Twitter, and news outlets. A meticulous data preprocessing phase guarantees data integrity, facilitating robust and streamlined analytical procedures. Through the implementation of sophisticated methodologies, including word frequency analysis, co-occurrence mapping, and sentiment classification, evolving trends, and latent patterns are uncovered within unstructured textual information. The resulting insights offer significant value to both commercial enterprises and academic researchers, empowering them to formulate informed, data-driven strategies grounded in contemporary trends. Furthermore, predictive models are developed based on identified trends, enabling proactive decision-making and forecasting of future shifts. The system’s modular design allows for easy integration with various data sources and analytical tools, enhancing its versatility and applicability across diverse domains. This also contributes to the development of scalable and efficient algorithms for real-time data processing, addressing the growing need for rapid insights in the age of information overload.