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Recognition of emotions, valence and arousal in large-scale multi-domain text reviews

Place of publication:

  • 9th Language & Technology Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics

 

Title:

Recognition of emotions, valence and arousal in large-scale multi-domain text reviews

 

Authors:

Jan Kocoń, Arkadiusz Janz, Piotr Miłkowski, Monika Riegel, Małgorzata Wierzba, Artur Marchewka, Agnieszka Czoska, Damian Grimling, Barbara Konat, Konrad Juszczyk, Katarzyna Klessa, Maciej Piasecki

 

Abstract:

In this article, we present a novel multidomain dataset of Polish text reviews. The data were annotated as part of a large study involving over 20,000 participants. A total of 7,000 texts were described with metadata, each text received about 25 annotations concerning polarity, arousal and eight basic emotions, marked on a multilevel scale. We present a preliminary approach to data labelling based on the distribution of manual annotations and to the classification of labelled data using logistic regression and bi-directional long short-term memory recurrent neural networks.

 

Link:

ResearchGate

 

Citation BibTeX:

@incollection { ,
title = “Recognition of emotions, valence and arousal in large-scale multi-domain text reviews”,
author = “Kocoń„, Jan and Janz, Arkadiusz and …, … and Juszczyk, Konrad and Klessa, Katarzyna and Piasecki, Maciej”,
editor = “Vetulani, Zygmunt and Paroubek, Patrick”,
booktitle = “Human Language Technologies as a Challenge for Computer Science and Linguistics”,
year = “2019”,
pages = “274-280”,
}

 

Full text:

LTC2019_Recognition_of_emotions__polarity_and_arousal_in_large_scale_multi_domain_text_reviews

 

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This article is collective work's result of different members of the Sentimenti team.