Detecting Hateful and Offensive Language using NLP

Challenge Background

The spread of hate speech and fake news is a serious side effect of expanding social networks. Most of the time covered by anonymity, social network users feel more comfortable speaking hate or disseminating fabricated information as opposed to real life, where they have to confront the consequences of what they say. All major social networks make an enormous effort to deal with such a problem, and machine learning is a powerful tool in this arena.

The Problem

We want to avoid the impacts of hate speech and fake news in our homes that would negatively affect our friends and families especially: children as they are the least expert with technology. As a result, we would use our technology experience to tackle this problem and provide a safe environment to them.

Goal of the Project

1. Train datasets
2. Carryout data pre-processing
3. Develop a Machine learning model
4. Use NLP and advanced Machine Learning
5. Develop an API to be used by individuals

Project Timeline

What you'll learn

1. The participants will deploy their data analysis skills: (such as data wrangling and preprocessing, problem solving using python,…etc.)
2. Practice Machine learning as well as neural nets background in a real-world project, in order to enrich their experience and skilling new fields (e.g. NLP and more advanced machine learning algorithms).
3. Offer a solution that may serve in solving the challenge they face.