Building Deep Learning Models to Detect Suicidal Posts in Modern Standard Arabic
Challenge Background
After the COVID-19 pandemic, many individuals started spending more time alone and online, leading them to start expressing their ideas through social media posts. In addition, several people lost their jobs leaving them with negative thoughts. The negative thoughts can quickly lead to suicidal thoughts.
The Problem
This project aims to build deep learning models to detect suicidal language in modern standard Arabic.
Due to the effects of COVID-19, negative ideas and impacts are increasing drastically. Moreover, a lot of individuals started to have suicidal thoughts due to the burden put on their shoulders. This project aims at detecting suicidal language to detect suicidal people in order to offer help to those who need it the most.
* Feel free to summarize the problem in your local language as well. This can help connect applicants to the problem. An example of how this was done can be seen here: https://omdena.com/projects/nlp-arabic/
Goal of the Project
- Collecting modern standard Arabic suicidal posts dataset
- Building deep learning models to detect the suicidal language
- Web Deployment
Project Timeline
- Dataset collection and Preprocessing - Data labeling
- Modeling - Getting initial results
- Sentiment Analysis Model - Web app for the model
- Web deployment
What you'll learn
- Data collection - Data cleaning - Modelling - Web deployment
First Omdena Local Chapter Project?
Beginner-friendly, but also welcomes experts
Education-focused
Duration: 4 to 8 weeks
Open-source
Your Benefits
Address a significant real-world problem with your skills
Build your project portfolio
Access paid projects (as an Omdena Top Talent)
Get hired at top organizations
Requirements
Good English
Suitable for AI/ Data Science beginners but also more senior collaborators
Learning mindset
Application Form
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