Mental health problems in young people have been following an upward trend over the last decade, which can cause long-term problems and unhealthy tendencies. In some cases, it can even cause self harm and suicide. As members of Generation Z, some of us are far too familiar with mental health issues, and we would like to use technology to help solve the problem.
What it does
Journaling and Gaining a better understanding of the self; two proven tactics to a better mental health. Our web application allows people to track their mental state in a calm journal-like environment, while using machine learning to find patterns in the fluctuations of their emotions to help them better understand themselves, and, well… Get Better. The Get Better website prompts people to record their emotions daily, with a “Dear journal,” format. They also record the time, the date, and special events that occurred that day. This entry is analyzed using sentimental analysis, a type of machine learning, to find the person’s specific mood at the time of the entry. Get Better then compares the entry with others to predict and inform the user of trends in their mood.
How we built it
HTML with CSS to create the website. The text analysis was created using NLTK and SkLearn.
Challenges we ran into
HTML and CSS were new to us so understanding the formatting and conventions of a new language were a main road block we had to overcome. In addition, doing the sentimental analysis, and then combining the Python with the HTML.
What we learned
- Machine Learning through Python
What's next for GetBetter
A couple of our next steps would include
- Graphs to visualize mood trends
- Calendar integration to remind user of daily entry
- Optimization of sentimental analysis and algorithm