Ben Burtenshaw


2020

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Sarcasm Detection Using an Ensemble Approach
Jens Lemmens | Ben Burtenshaw | Ehsan Lotfi | Ilia Markov | Walter Daelemans
Proceedings of the Second Workshop on Figurative Language Processing

We present an ensemble approach for the detection of sarcasm in Reddit and Twitter responses in the context of The Second Workshop on Figurative Language Processing held in conjunction with ACL 2020. The ensemble is trained on the predicted sarcasm probabilities of four component models and on additional features, such as the sentiment of the comment, its length, and source (Reddit or Twitter) in order to learn which of the component models is the most reliable for which input. The component models consist of an LSTM with hashtag and emoji representations; a CNN-LSTM with casing, stop word, punctuation, and sentiment representations; an MLP based on Infersent embeddings; and an SVM trained on stylometric and emotion-based features. All component models use the two conversational turns preceding the response as context, except for the SVM, which only uses features extracted from the response. The ensemble itself consists of an adaboost classifier with the decision tree algorithm as base estimator and yields F1-scores of 67% and 74% on the Reddit and Twitter test data, respectively.

2019

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Offence in Dialogues: A Corpus-Based Study
Johannes Schäfer | Ben Burtenshaw
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)

In recent years an increasing number of analyses of offensive language has been published, however, dealing mainly with the automatic detection and classification of isolated instances. In this paper we aim to understand the impact of offensive messages in online conversations diachronically, and in particular the change in offensiveness of dialogue turns. In turn, we aim to measure the progression of offence level as well as its direction - For example, whether a conversation is escalating or declining in offence. We present our method of extracting linear dialogues from tree-structured conversations in social media data and make our code publicly available. Furthermore, we discuss methods to analyse this dataset through changes in discourse offensiveness. Our paper includes two main contributions; first, using a neural network to measure the level of offensiveness in conversations; and second, the analysis of conversations around offensive comments using decoupling functions.

2018

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Proceedings of the 3rd Workshop on Computational Creativity in Natural Language Generation (CC-NLG 2018)
Hugo Gonçalo Oliveira | Ben Burtenshaw | Raquel Hervás
Proceedings of the 3rd Workshop on Computational Creativity in Natural Language Generation (CC-NLG 2018)

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A Brief Introduction to Natural Language Generation within Computational Creativity
Ben Burtenshaw
Proceedings of the 3rd Workshop on Computational Creativity in Natural Language Generation (CC-NLG 2018)

2017

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Proceedings of the Workshop on Computational Creativity in Natural Language Generation (CC-NLG 2017)
Hugo Gonçalo Oliveira | Ben Burtenshaw | Mike Kestemont | Tom De Smedt
Proceedings of the Workshop on Computational Creativity in Natural Language Generation (CC-NLG 2017)

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Synthetic Literature: Writing Science Fiction in a Co-Creative Process
Enrique Manjavacas | Folgert Karsdorp | Ben Burtenshaw | Mike Kestemont
Proceedings of the Workshop on Computational Creativity in Natural Language Generation (CC-NLG 2017)