erYash15/Real-or-Not-NLP-with-Disaster-Tweets
Sentiment analysis of the dataset of twitter disaster tweets and predicting is it the actual disaster or metaphorically expressed as disaster.
This project helps classify tweets to determine if they describe a real disaster or use disaster-related language metaphorically. You provide a collection of tweets, and it identifies which ones are genuine disaster reports and which are not. This is useful for emergency responders, news agencies, or social media analysts monitoring events.
No commits in the last 6 months.
Use this if you need to quickly filter large volumes of social media data to identify actual disaster communications amidst colloquial or unrelated mentions.
Not ideal if you require real-time, high-precision detection for life-critical disaster response without further human verification, or if your dataset is not Twitter-based.
Stars
8
Forks
1
Language
Jupyter Notebook
License
—
Category
Last pushed
Jan 31, 2021
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/erYash15/Real-or-Not-NLP-with-Disaster-Tweets"
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.