GitHub - sanjuatwal/Data-Analysis-and-Data-Management-on-Suicid…

I developed a project aimed at analyzing the deteriorating mental health of people by analyzing data from the popular networking website Reddit pre and post lockdown. The goal was to fetch data from the keywords belonging to a category of tweets r/depression and r/suicide-watch on Reddit and train a model to predict if a post or tweet falls in these 2 categories.

During the pandemic, people faced mental health issues and were struggling to cope up locked in home. They sought social media like Reddit where there are 2 subreddits dedicated to depression and suicide, specifically dedicated to helping people in these situations. To address the large amount of data available and the lack of it being filtered out, I developed an idea to train a model that could predict if any post or tweet falls under the category of being either suicidal or depressing, so it could be filtered out and immediate help could also be made available through online medium for whoever posted so.

To accomplish the project goal, I used Reddit's API to fetch data from r/depression and r/suicide-watch, trained a predictive model to identify posts that fall into those categories, collected data, and analyzed and filtered tweets as required. I also used aspects of data visualization and big data analysis to analyze the collected data.

Through this project, I was able to develop a model that can predict if a post or a tweet falls in the categories of depression or suicide. The model also helped in lemmatization of important words in tweets and posts.

This project was motivated by the fact that people post a lot of content online and are very vocal about their mental health. The project highlights the importance of predictive data analysis and the potential of technology to provide immediate help to people in need. The dataset obtained from this project can also be used for future research and development of models such as Google's State-of-the-Art NLP model BERT.