  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.
