عکس omidrohanian
Code and data used for participation in SemEval-2018 Task 3: "Irony detection in English tweets"Jupyter Notebook
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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}
}