Emotional Hub

EmotionalHub was inspired by my first break up — a challenging personal experience that came to highlight the significant impact of social media on our emotions. I noticed how these platforms intensified feelings of sadness by continually presenting similar content to maximize viewer engagement. This experience made me realize the need for a platform that could counteract this effect. 

 

With this project, we are committed to aids self-awareness, enhance interpersonal communications, and transform our interactions with digital content in a way that supports mental health.

 

Leveraging machine learning, EmotionalHub analyzes emotional expressions in text and provides real-time feedback, helping people to understand and navigate their emotional trends. In specific, we combine  VAD model and CrowdFlower model to detect emotions. Both of they are trained, and the post recommendation algorithm will connect the emotions detected with user intentions. In application, the algorithm will be leveraged as the connection between the home page (where the user selects their intention) to the feed page, where the user sees posts from other users. Different chosen intentions bring up different posts which correspond to that intention as predicted by the algorithm.

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As an open-source initiative, EmotionalHub invites developers to contribute, thereby broadening the tool's impact and improving emotional intelligence resources for a diverse audience. Please be aware that as of 2023, the Heroku deployment of the project is no longer active.

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