|Title||EmojiNet: Building a Machine Readable Sense Inventory for Emoji|
|Publication Type||Conference Proceedings|
|Year of Publication||2016|
|Authors||Sanjaya Wijeratne, Lakshika Balasuriya, Amit Sheth, Derek Doran|
|Editor||Emma Spiro, Yong-Yeol Ahn|
|Conference Name||8th International Conference on Social Informatics (SocInfo 2016)|
|Publisher||Springer International Publishing|
|Conference Location||Bellevue, WA|
|Keywords||Emoji Analysis, Emoji Sense Disambiguation, EmojiNet|
Emoji are a contemporary and extremely popular way to enhance electronic communication. Without rigid semantics attached to them, emoji symbols take on different meanings based on the context of a message. Thus, like the word sense disambiguation task in natural language processing, machines also need to disambiguate the meaning or ‘sense’ of an emoji. In a first step toward achieving this goal, this paper presents EmojiNet, the first machine readable sense inventory for emoji. EmojiNet is a resource enabling systems to link emoji with their context-specific meaning. It is automatically constructed by integrating multiple emoji resources with BabelNet, which is the most comprehensive multilingual sense inventory available to date. The paper discusses its construction, evaluates the automatic resource creation process, and presents a use case where EmojiNet disambiguates emoji usage in tweets. EmojiNet is available online for use at http://emojinet.knoesis.org.
|Additional Information|| |
In the reviewers’ words:
"The representation of emojis with a tuple of 8 field is well designed and puts in a single place almost all the information available about emojis in previous dictionaries, reported in the previous work section. The authors evaluate the resource under the aspects of image detection/alignment and word sense disambiguation. both evaluation tasks are performed correctly."