Creating a Dataset for Multilingual Fine-grained Emotion-detection Using Gamification-based Annotation

Emily Sofi Öhman, Jörg Tiedemann, Timo Untamo Honkela, Kaisla S A Kajava

Forskningsoutput: Kapitel i bok/rapport/konferenshandlingKonferensbidragVetenskapligPeer review

Sammanfattning

This paper introduces a gamified framework for fine-grained sentiment analysis and emotion detection. We present a flexible tool, Sentimentator, that can be used for efficient annotation based on crowd sourcing and a selfperpetuating gold standard. We also present a novel dataset with multi-dimensional annotations of emotions and sentiments in movie subtitles that enables research on sentiment preservation across languages and the creation of robust multilingual emotion detection tools. The tools and datasets are public and opensource and can easily be extended and applied for various purposes.
Originalspråkengelska
Titel på värdpublikationProceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
RedaktörerAlexandra Balahur, Saif M. Mohammad, Veronique Hoste, Roman Klinger
Antal sidor7
UtgivningsortStroudsburg
FörlagThe Association for Computational Linguistics
Utgivningsdatum31 okt. 2018
Sidor24-30
ISBN (elektroniskt)9781948087803
DOI
StatusPublicerad - 31 okt. 2018
MoE-publikationstypA4 Artikel i en konferenspublikation
EvenemangWorkshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis - Brussels, Belgien
Varaktighet: 31 okt. 201831 okt. 2018
Konferensnummer: 9

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