Irony Detection in English Tweets

Code and the data used with regard to experiments in the paper WLV at SemEval-2018 Task 3: Dissecting Tweets in Search of Irony.

Dependencies:

• Ekphrasis (pip install ekphrasis)
• Stanford CoreNLP
• Pycore NLP (pip install pycorenlp)
• Sklearn / scikit-learn (pip install scikit-learn)
• NLTK (pip install nltk)
  • nltk.download('wordnet')
  • nltk.download('averaged_perceptron_tagger')
  • nltk.download('sentiwordnet')
• Gensim (pip install gensim)

If you use the code for your project, please cite the following paper (link to PDF):

@inproceedings{rohanian2018wlv,
  title={WLV at SemEval-2018 Task 3: Dissecting Tweets in Search of Irony},
  author={Rohanian, Omid and Taslimipoor, Shiva and Evans, Richard and Mitkov, Ruslan},
  booktitle={Proceedings of The 12th International Workshop on Semantic Evaluation},
  pages={553--559},
  year={2018}
}