irony_detection
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Code and data used for participation in SemEval-2018 Task 3: "Irony detection in English tweets"
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}
}