Detecting Potentially Harmful and Protective Suicide-related Content on Twitter

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Deep LearningTwitterSuicideML
Overview

TwitterSuicideML

Scripts for reproducing the Machine Learning analysis of the paper: Detecting Potentially Harmful and Protective Suicide-related Content on Twitter: Machine Learning Classification of Tweets

  1. clone this repository: git clone https://github.com/HubertBaginski/TwitterSuicideML.git

  2. Get the dataset with tweet text, and put it in the folder "data" within the repository folder. Option a: write to us to get the training dataset including the text of tweets: [email protected] Option b: rehydrate the tweets based on the tweet IDs in the dataset

  3. Create a virtual environment "TwittersuicideML": conda create --name TwitterSuicideML

  4. Activate the environments after all packages are installed: conda activate TwittersuicideML

  5. Install all the packages we used, from within the repository folder: pip install -r requirements.txt

  6. Open Jupyter Notebook or Juptyer Lab

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