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Goal of this project was to classify whether a tweet was about a natural disaster or not.

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Natural Disaster Twitter Prediction

Problem statement:

The world we live in is more connected than ever, thanks to the internet and social media platforms. Twitter is one such platform where people share their thoughts whether it is about everyday random musings or about something personal and serious. Given the enormity of tweets at any given point in time, it is impossible is manually look at each and every tweet to decide if its about a natural disaster or not.

Value for stakeholders:

The target users of this A.I. based system are first responders such as paramedics, police and firefighters as well as news agencies and disaster relief organizations. These stakeholders are likely to find value in a project like this.

Proposed solution:

Use A.I. and machine learning algorithms that surveil tweets and alert stakeholders whether there is an emergency or natural disaster situation. Check out our presentation PDF in this repo or Google presentation and associated video walkthrough to learn more about the details of the implementation and high level overview of the system architecture.

  • Google presentation

https://docs.google.com/presentation/d/1YJaoF6WqfYPk6ELB8EWfyXi8ltviLl1PUqf-Qi4UrkU/edit?usp=sharing

  • Video walkthrough

https://pitt.zoom.us/rec/share/opU2cpzR60hJftbjsEDyZ-0-DsfIT6a80SJIrKENmEr0NXTGgbDh8I7DDxOfHxFj

  • YouTube video

https://www.youtube.com/watch?v=TOKwj5pCW_k

Reference:

This A.I. system is based on a kaggle competition called, "Real or Not? NLP with Disaster Tweets" (https://www.kaggle.com/c/nlp-getting-started).