EmojiNet: Building a Machine Readable Sense Inventory for Emoji

@article{Wijeratne2016EmojiNetBA,
  title={EmojiNet: Building a Machine Readable Sense Inventory for Emoji},
  author={Sanjaya Wijeratne and Lakshika Balasuriya and Amit P. Sheth and Derek Doran},
  journal={Proceedings. International Workshop on Social Informatics},
  year={2016},
  volume={10046},
  pages={527-541}
}
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… CONTINUE READING
Highly Cited
This paper has 17 citations. REVIEW CITATIONS
Recent Discussions
This paper has been referenced on Twitter 12 times over the past 90 days. VIEW TWEETS

6 Figures & Tables

Topics

Statistics

0102020172018
Citations per Year

Citation Velocity: 10

Averaging 10 citations per year over the last 2 years.

Learn more about how we calculate this metric in our FAQ.