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Projects / Local Chapter Project

Building Deep Learning Models to Detect Suicidal Posts in Modern Standard Arabic

Start Date: October 20, 2021 | 4 years ago


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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

1

- Dataset collection and Preprocessing - Data labeling

2

- Modeling - Getting initial results

3

- Sentiment Analysis Model - Web app for the model

4

- 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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