Emotion and Event Detentions in Python

Abstract -

The focus of this research is to build a cloud based architecture to analyze the correlation between social media data and events predictions. From analytical point of view this study refurbishes the viability of models that treat public mode and emotion as a unitary phenomenon and suggest the needs to analyze those in predicting the market event status of the respective companies. The major significance of this research is the normalization and the conversion process that has utilized vector array list which thereby strengthen the conversion process and make the cloud storing an easy process. Furthermore, the experimental results demonstrate its improved performance over the factor of emotion analysis and synthesizing in the process of prediction to extract patterns in the way events behave and respond to external stimuli and vice versa.