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

Emily Öhman, Kaisla Kajava, Jörg Tiedemann, Timo Honkela

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

20 Sitaatiot (Scopus)

Abstrakti

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 self-perpetuating 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 open-source and can easily be extended and applied for various purposes.

AlkuperäiskieliEnglanti
OtsikkoWASSA 2018 - 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop
KustantajaAssociation for Computational Linguistics
Sivut24-30
Sivumäärä7
ISBN (elektroninen)9781948087803
TilaJulkaistu - 2018
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaWorkshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis - Brussels, Belgia
Kesto: 31 lokak. 201831 lokak. 2018
Konferenssinumero: 9

Workshop

WorkshopWorkshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
Maa/AlueBelgia
KaupunkiBrussels
Ajanjakso31/10/201831/10/2018

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