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The ability to automatically process, derive meaning, and interpret text fused with emoji will be essential as society embraces emoji as a standard form of online communication. Yet the pictorial nature of emoji, the fact that (the same) emoji may be used in different contexts to express different meanings, and that emoji are used in different cultures over the world who interpret emoji differently, make it especially difficult to apply traditional Natural Language Processing (NLP) techniques to analyze them. This talk presents the creation of EmojiNet, the first machine-readable emoji sense repository that is designed by extracting emoji meanings from reliable online web sources and its applications for understanding emoji meaning in the social media text. It discusses how EmojiNet enables using NLP techniques to solve novel emoji research problems including emoji similarity and emoji sense disambiguation. A live demo of EmojiNet is available at http://emojinet.knoesis.org