Automatic Detection of Irony and Humour in Twitter

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Reference

Francesco Barbieri and Horacio Saggion: Automatic Detection of Irony and Humour in Twitter. In: Computational Creativity 2014 ICCC 2014, 155-162.

DOI

Abstract

Irony and humour are just two of many forms of figurative language. Approaches to identify in vast volumes of data such as the internet humorous or ironic statements is impor- tant not only from a theoretical view point but also for their potential applicability in social networks or human-computer interactive systems. In this study we investigate the auto- matic detection of irony and humour in social networks such as Twitter casting it as a classification problem. We propose a rich set of features for text interpretation and representation to train classification procedures. In cross-domain classification experiments our model achieves and improves state-of-the-art performance.

Extended Abstract

Bibtex

@inproceedings{
author = {Francesco Barbieri and Horacio Saggion},
title = {Automatic Detection of Irony and Humour in Twitter},
booktitle = {Proceedings of the Fifth International Conference on Computational Creativity},
series = {ICCC2014},
year = {2014},
month = {Jun},
location = {Ljubljana, Slovenia},
pages = {155-162},
url = {http://computationalcreativity.net/iccc2014/wp-content/uploads/2014/06//9.2_Barbieri.pdf, http://de.evo-art.org/index.php?title=Automatic_Detection_of_Irony_and_Humour_in_Twitter },
publisher = {International Association for Computational Creativity},
keywords = {computational, creativity},
}

Used References

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