EmojiNet: Building a Machine Readable Sense Inventory for Emoji

  • Sanjaya Wijeratne
  • Lakshika Balasuriya
  • Amit Sheth
  • Derek Doran
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10046)


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


EmojiNet Emoji analysis Emoji sense disambiguation 



We are grateful to Sujan Perera for thought-provoking discussions on the topic. We acknowledge partial support from the National Institute on Drug Abuse (NIDA) Grant No. 5R01DA039454-02: “Trending: Social Media Analysis to Monitor Cannabis and Synthetic Cannabinoid Use”, National Institutes of Health (NIH) award: MH105384-01A1: “Modeling Social Behavior for Healthcare Utilization in Depression”, and Grant No. 2014-PS-PSN-00006 awarded by the Bureau of Justice Assistance. The Bureau of Justice Assistance is a component of the U.S. Department of Justice’s Office of Justice Programs, which also includes the Bureau of Justice Statistics, the National Institute of Justice, the Office of Juvenile Justice and Delinquency Prevention, the Office for Victims of Crime, and the SMART Office. Points of view or opinions in this document are those of the authors and do not necessarily represent the official position or policies of the U.S. Department of Justice, NIH or NIDA.


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Sanjaya Wijeratne
    • 1
  • Lakshika Balasuriya
    • 1
  • Amit Sheth
    • 1
  • Derek Doran
    • 1
  1. 1.Kno.e.sis CenterWright State UniversityDaytonUSA

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