Positive Pulse | Devpost

Wordcloud of our nlp model for tweets related to burnout

Inspiration

As we know that healthcare provider's burnout is a serious issue that affects many people working in the healthcare industry. It can result from a combination of factors, including long and demanding work hours, high levels of stress and responsibility, exposure to traumatic events, and a lack of control over one's work environment. Tweeting about burnout can provide a sense of community and help healthcare providers feel less isolated in their struggles. So, we are trying to find the tweets which are related to burnout and give them a positive automated reply so they can feel a little sense of relaxation.

What it does

With Positive Pulse we try to help and keep the healthcare providers motivated and not depressed and burnout. It is a small step on our part to keep the force that keeps us healthy and feel appreciated. Positive Pulse on Twitter replies to tweets which sound depressing or burnout with a positive appreciative tweet in return.

How we built it

We used Python and Tableau to get data-driven insights on burnout in the healthcare industry. We used NLP tools, sentiment intensity analyzer and tf-idf vectorizer to classify the tweet as a burnout or non-burnout tweet. Then, we created visuals for the same using Wordcloud to find the words occurring most in burnout tweets.

Challenges we ran into

Getting a dataset. It was challenging to find the proper dataset needed for the problem. This took quite a bit of our time.

Accomplishments that we're proud of

First time building an NLP model, learning to use Wix, getting things done in 36 hours, and solving problems as they appear to the best of our abilities.

What we learned

We learned a lot about burnout in the healthcare industry, gaining new insights on the topic. We learnt a ton of new libraries, packages and tools.

What's next for Positive Pulse

Creating a Twitter bot that finds burnout tweets by healthcare providers and replies them with a positive, energetic and insightful reply according to their tweet.