Code for the sarcasm detection system described in the paper Modelling Context with User Embeddings for Sarcasm Detection in Social Media [[paper] (https://arxiv.org/abs/1607.00976)] [[bib] ()]

The CNN implemention was forked from [Giuseppe Attardi] (https://github.com/attardi/CNN_sentence) (which was forked from [Yoon Kim] (https://github.com/yoonkim/CNN_sentence))

pre-requisites:

• my_utils -> https://github.com/samiroid/utils
• pre-trained word embeddings (e.g. Skip-gram)
• user embeddings -> The embeddings we used can be found here. If you want to train your own embeddings you can use the code available here.

requirements:

• python >= 2.7
• numpy
• theano

To comply with Twitter policies we can only share the msg ids. These can be found in the file bamman_redux_ids.csv

1. clone or download the [my_utils] (https://github.com/samiroid/utils) module and place it under the folder code
2. run prepare.sh with the paths to the utils module and the word embeddings: ./prepare.sh PATH_TO_WORD_EMBEDDINGS PATH_TO_USER_EMBEDDINGS
3. run sarcasm_cnn.sh

4. run crossfolds.sh