Vujavujavuja/Disaster_Tweet_Classification
This is a no-frills Multinomial Naive Bayes classifier built from scratch in Python to quickly determine if a tweet is reporting a real disaster or just some random noise. It's simple, fast, and uses a basic Bag-of-Words approach after a standard text cleaning routine.
Stars
1
Forks
—
Language
Python
License
—
Category
Last pushed
Oct 28, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/Vujavujavuja/Disaster_Tweet_Classification"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
wri-dssg-omdena/policy-data-analyzer
Building a model to recognize incentives for landscape restoration in environmental policies...
IliaZenkov/NLP-keras-nltk-lime
Classification of tweets pertinent to disaster events. NLP basics with a focus on text...
deepmancer/tweet-disaster-detection
fine-tuned BERT and scikit-learn models for real-time classification of disaster-related tweets,...
wang0324/TwitterRelevanceClassification
Classifies if a tweet is relevant to a disaster or not
kushv16/Disaster_Tweets_Analysis
Project based on Natural Language Processing to identify if the given tweet indicates a disaster.