Análisis de sentimiento en redes sociales a través de un marco de Big data

Currently, data analysis has become the ideal tool for organizations that want to know what people’s opinion is about a product, an organization, or an event. Social networks allow identifying the opinions and preferences of their users, through the information contained in the publications they make. For this, this work proposes the design of a framework for sentiment analysis for social networks through Apache Spark. This implementation allows the user’s assessment of a brand, organization, or topic. In the design, Big data architecture is used for the analysis of requirements through user stories. This information is transformed into knowledge that organizations use to generate plans that allow them to improve their processes and therefore the image they generate towards their clients.