emoji classification

What is emoji similarity model?
Fig. 1. Sample Unicode Description for Emoji. One of the remarkable studies in emoji classification is the study by Pohl et al. (2017) that proposed an emoji similarity model that automatically creates emoji-pairs and optimize emoji ordering to retrieve a fitting emoji based on the emoji or text user entered in the applications.
Where do emoji charts come from?
These are derived from the data files for UTS #51, Unicode Emoji, and the annotation and ordering data from the Unicode CLDR project . For a set of slides about emoji, see Emoji Slides. While these charts use a particular version of the Unicode Emoji data files , the images and format may be updated at any time.
How many facial emojis are there?
According to Emojipedia 9, the Apple platform (ver. iOS 14.6) has implemented 94 kinds of human facial emojis thus far. However, in comparison, previous studies have explored an insufficient number of facial emojis. For example, Jaeger et al. 5 and Phan et al. 10 used only a set of 33 and 6 facial emotions to assess emotional states, respectively.
How emoji classification works?
With the surging popularity of Emojis, the researchers in the area of Emotion Classification strive to understand the emotion correlated to each Emoji. Two of the most the successful approaches in emoji analysis rely on: 1) official Unicode description and 2) manually built emoji lexicons.

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PDF	Multi-class Sentiment Classification on Twitter using an Emoji - DiVA As emojis are becoming more popular to use in text-based commu- nication this thesis investigates the feasibility of an emoji training heuristic for multi-class

PDF	Classifying the Informative Behaviour of Emoji in Microblogs The best classification model achieved an F-score of 0 7 In this paper we shortly present the corpus, and we describe the classification experiments, explain the

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