EmojiNet: An Open Service and API for Emoji Sense Discovery

TitleEmojiNet: An Open Service and API for Emoji Sense Discovery
Publication TypeConference Paper
Year of Publication2017
AuthorsSanjaya Wijeratne, Lakshika Balasuriya, Amit Sheth, Derek Doran
Conference Name11th International AAAI Conference on Web and Social Media (ICWSM 2017)
Date PublishedMay
Conference LocationMontreal, Canada
KeywordsEmoji Analysis, Emoji Sense Disambiguation, Emoji Similarity, EmojiNet

This paper presents the release of EmojiNet, the largest machine-readable emoji sense inventory that links Unicode emoji representations to their English meanings extracted from the Web. EmojiNet is a dataset consisting of: (i) 12,904 sense labels over 2,389 emoji, which were extracted from the web and linked to machine-readable sense definitions seen in BabelNet; (ii) context words associated with each emoji sense, which are inferred through word embedding models trained over Google News corpus and a Twitter message corpus for each emoji sense definition; and (iii) recognizing discrepancies in the presentation of emoji on different platforms, specification of the most likely platform-based emoji sense for a selected set of emoji. The dataset is hosted as an open service with a REST API and is available at http://emojinet.knoesis.org/. The development of this dataset, evaluation of its quality, and its applications including emoji sense disambiguation and emoji sense similarity are discussed.

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