Natural Language Processing With Disaster Tweets

This Omdena Local Chapter Challenge runs for 8 weeks and is a unique experience to try and grow your skills in a collaborative and safe environment with a diverse mix of people from all over the world. 

You will work on solving a local problem, initiated by Giza, Egypt Chapter.

The problem

The analysis of social media data during natural disasters can be challenging due to the sheer volume of data generated and the need to quickly identify relevant information. Additionally, tweets are often short, informal, and contain non-standard language, making them difficult to analyze using traditional NLP techniques. As a result, there is a need for more advanced NLP techniques that can accurately classify disaster-related tweets and extract relevant information in real-time.

The dataset provided for this challenge consists of a collection of tweets that have been labeled as either “disaster” or “not disaster”. The goal is to build a model that can learn to distinguish between the two classes based on the text content of the tweets. The challenge is designed to test participants’ skills in natural language processing (NLP) and machine learning. It requires them to preprocess the text data, perform feature engineering, and build a model that can accurately classify tweets.

The goals

The goals of Natural Language Processing with Disaster Tweets research are:

• To explore the current state-of-the-art in NLP techniques for disaster tweet analysis, including tweet classification and sentiment analysis.
• Text Preprocessing.
• Model Development: We will try to apply machine learning and deep learning models including RNN and Transformers.
• Evaluate Model.
• Compare the performance of machine learning and deep learning (RNNS and Transformers).
• App Deployment.

Why join? The uniqueness of Omdena Local Chapter Challenges

Omdena Local Chapter Challenges are not a competition or hackathon but a real-world project that will grow your experience to a new level.

A unique learning experience with the potential to make an impact through the outcome of the project. You will go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join the global and collaborative community of Omdena with tons of benefits to accelerate your career.

Read more on how Omdena´s Local Chapters work