Dynamic Visualization of Emotional States Using Natural Language Processing and Graph Algorithms

The research investigates the visualization of data in order to represent changes in emotions using daily journal entries consisting of a single sentence. In addition, each journal entry contains an adjective that symbolizes what the dominant feeling was that day and the cause behind it. The emotional expressions are grouped and coded into six basic emotions by Natural Language Processing Toolkit (NLTK), while nodes are color-coded based on the frequency and intensity of these categories. Advanced technologies such as Sigma.js have been used for creating interactive dynamic visualizations involving darkening nodes according to their frequency so as to enhance user attention and learning. The application has a provision where users can enter their own data, which creates personalized emotion graphs. Developments include establishing a back-end for direct recording of daily journals on the platform, thus allowing the tracking and contemplation of emotional patterns over time by users themselves. By allowing people to track their emotions easily, this artistic experience wants to provide a simple but playful way to monitor mental health, hence it could also be useful in counseling or personal psychological care assistance.