This is the accompanying code for Searching for PETs: An Analysis on Using Distributional and Sentiment-Based Methods to Find Potentially Euphemistic Terms.

To download the code, there are two options:

• Using git clone may be the most straightforward. The word2vec models used are over the Github size limit (~3GB combined), so I used Git LFS (Large File Storage) to upload them. This means that if you just download the repository as a .zip file, some of the files will only be pointers to where they're stored on the Git cloud storage. On the other hand, using git clone seems to automatically download the files from the cloud storage during the cloning process.
• If git clone doesn't work for you, the files can also be found here. Unzip them into the data file, and it should work.

There are two notebooks. Single_Sentence_Euph_Detection.ipynb is the one which is intended for users to try. To use it, run the first 3 chunks, and then use the fourth chunk to test out your input text. Note that there are some required packages, which I note (along with these instructions) in the notebook.

The other notebook, Euph_Detection_6-11.ipynb, is the one used to generate the results shown in the paper, and is mostly for reference.

Please let us know if anything doesn't work for you. If it's needed, the code will be continuously updated to improve performance/ease of use.