Journaling is a psychologically proven helpful tool for recovery from stressors. One of the key benefits of journaling is increased emotional/mood awareness, which allows one to channel negative energy into positive energy and growth. The benefits of journaling can be applied to other texts, through mood analysis. Therefore, by writing public posts, users will be able to gain additional insight regarding their emotions.
What it does
mood.ai is a mood tracking application that takes in information from a users Facebook profile and text from public posts. The text information is then processed using a model and categorized based on five emotions: joy, sadness, anger, fear and surprise . A suicide tendency index is also allocated to each post.
The _ mood.ai _ application displays this information for a users post in a particular day in a five petalled flower design, where each petal representing one mood. A translucent triangle stretches above these petals based on the mood indexes of the day. A calendar on the top tracks longitudinal data for each of the moods that can be selected by spinning the flower.
How I built it
_ mood.ai _ was by sorting data from API's into categories. Inputed data could then be compared to pre-existing data such that indexes could be allocated to these categories using binary trees.
Challenges I ran into
Difficulties with incorporating Facebook API.
Accomplishments that I'm proud of
Learning how to process and categorize data.
What I learned
Basics of neuro-networks and binary trees.
What's next for _ mood.ai _
_ mood.ai _ can also be applied to a Journaling App, which could incorporate mood and suicide tendency to provide additional emotional insight for the user.
Data from _ mood.ai _ can also be personally disclosed to psychologists to track if a patient is recovering or digressing.