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Earthquake Aid Classification Dataset
Data Science and Analytics
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Free
About
This dataset provides a collection of 500 tweets related to the earthquake that occurred in Turkey on 6 February 2023. The earthquake was a significant event with a magnitude of 7.5, causing considerable damage and loss. The tweets are organised into two distinct classes to aid in disaster response and relief efforts. This dataset is designed to be a training resource for developing machine learning models capable of assisting in emergency situations by classifying social media content.
Columns
- Tweets: Contains the text content of the social media posts.
- Class: Represents a categorical label assigned to each tweet.
- Class 1: Denotes tweets from individuals affected by the earthquake, typically asking for assistance and providing details such as their location or contact information. This class comprises 300 tweets.
- Class 0: Includes tweets that may contain keywords similar to those in Class 1, such as "earthquake," "food," or "blanket," but are not direct appeals for help. This class includes 150 such tweets, with an additional 50 tweets that are unrelated to the earthquake.
Distribution
The dataset comprises 500 tweets. The data file is typically in a CSV format. Within the dataset, Class 1 is represented by 300 tweets, and Class 0 consists of 200 tweets.
Usage
This dataset is ideally suited for training machine learning models aimed at enhancing disaster response and relief operations. It can be utilised to develop systems that automatically categorise tweets based on their content, identify areas in critical need of aid, and forecast the resources required for effective relief efforts.
Coverage
The dataset focuses on tweets related to the earthquake that struck Turkey on 6 February 2023. It captures information from people affected by this specific event, offering insights into the immediate aftermath and needs following a natural disaster in the region.
License
CC0
Who Can Use It
This dataset is particularly useful for researchers and practitioners in data science, machine learning, and humanitarian aid. They can leverage this data to build and refine models that contribute to more efficient and effective disaster response systems.
Dataset Name Suggestions
- Turkey Earthquake Relief Tweets
- Turkish Disaster Response Tweets
- Earthquake Aid Classification Dataset
- Turkey 2023 Earthquake Social Media Data
- Disaster Relief Tweet Classifier Dataset
Attributes
Original Data Source: Turkey Earthquake Relief Tweets Dataset
QUALITY