Sentimentator: Gamifying fine-grained sentiment annotation

Emily Öhman, Kaisla Kajava

Research output: Contribution to journalConference articlepeer-review

4 Citations (Scopus)

Abstract

We introduce Sentimentator; a publicly available gamified web-based annotation platform for fine-grained sentiment annotation at the sentence-level. Sentimentator is unique in that it moves beyond binary classification. We use a tendimensional model which allows for the annotation of 51 unique sentiments and emotions. The platform is gamified with a complex scoring system designed to reward users for high quality annotations. Sentimentator introduces several unique features that have previously not been available, or at best very limited, for sentiment annotation. In particular, it provides streamlined multi-dimensional annotation optimized for sentence-level annotation of movie subtitles. Because the platform is publicly available it will benefit anyone and everyone interested in finegrained sentiment analysis and emotion detection, as well as annotation of other datasets.

Original languageEnglish
Pages (from-to)98-110
Number of pages13
JournalCEUR Workshop Proceedings
Volume2084
Publication statusPublished - 2018
Externally publishedYes
Event3rd Conference on Digital Humanities in the Nordic Countries, DHN 2018 - Helsinki, Finland
Duration: 2018 Mar 72018 Mar 9

ASJC Scopus subject areas

  • Computer Science(all)

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