raklugrin01/Disaster-Tweets-Analysis-and-Classification
Analysing Disaster related tweets dataset and build a classifier using deep learning and deploy it using Heroku
This project helps disaster relief organizations and news agencies quickly identify real emergency tweets from general chatter. It takes raw Twitter data and processes it to filter out irrelevant information, then classifies tweets as either 'disaster' or 'not disaster'. The output is a categorized feed of tweets, enabling responders and journalists to focus on actionable information during critical events.
No commits in the last 6 months.
Use this if you need to programmatically monitor Twitter feeds to distinguish genuine disaster alerts from false alarms or unrelated posts in real-time.
Not ideal if you need to analyze highly specialized or niche types of emergency data beyond general disaster tweets, or if you require an extremely high volume, real-time streaming solution without any latency tolerance.
Stars
10
Forks
3
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Nov 25, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/raklugrin01/Disaster-Tweets-Analysis-and-Classification"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Hironsan/HateSonar
Hate Speech Detection Library for Python.
t-davidson/hate-speech-and-offensive-language
Repository for the paper "Automated Hate Speech Detection and the Problem of Offensive...
franciellevargas/HateBR
HateBR is the first large-scale expert annotated dataset of Brazilian Instagram comments for...
rishabhmisra/News-Headlines-Dataset-For-Sarcasm-Detection
High quality dataset for the task of Sarcasm Detection
b4k0/CBDA
Cyber Bullying Detection Application (CBDA)