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Sentiment of Emojis.

Petra Kralj Novak1, Jasmina Smailović1, Borut Sluban1

  • 1Jožef Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia.

Plos One
|December 8, 2015
PubMed
Summary

Researchers created the first emoji sentiment lexicon, the Emoji Sentiment Ranking, revealing most emojis, especially popular ones, carry positive emotions. This resource aids automated sentiment analysis across languages.

Area of Science:

  • Computational Linguistics
  • Social Media Analysis
  • Affective Computing

Background:

  • Emojis are increasingly prevalent in digital communication, serving as Unicode graphic symbols for expressing concepts.
  • Unlike traditional emoticons, the emotional content of hundreds of emojis remains largely unexplored.
  • Understanding emoji sentiment is crucial for accurate social media and communication analysis.

Purpose of the Study:

  • To develop the first comprehensive emoji sentiment lexicon, named the Emoji Sentiment Ranking.
  • To create a sentiment map of the 751 most frequently used emojis.
  • To investigate the emotional content and usage patterns of emojis in online communication.

Main Methods:

  • Collected and analyzed over 1.6 million tweets across 13 European languages, with 83 human annotators labeling sentiment polarity.

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  • Computed emoji sentiment based on the sentiment of the tweets in which they appeared.
  • Developed a novel visualization technique, the sentiment bar, for representing emoji sentiment.

    • Main Results:

    • The Emoji Sentiment Ranking reveals that the majority of emojis, particularly the most popular ones, exhibit positive sentiment.
    • Tweets containing emojis show a significantly different sentiment distribution compared to tweets without emojis.
    • Higher inter-annotator agreement was observed for tweets containing emojis, suggesting clearer emotional expression.
    • Emojis are predominantly used at the end of tweets, with sentiment polarity increasing with their distance from the start.

    Conclusions:

    • The Emoji Sentiment Ranking serves as a valuable, language-independent resource for automated sentiment analysis.
    • Emoji usage patterns and sentiment polarity are consistent across the 13 European languages studied.
    • The study provides a formalization of sentiment and a new visualization method for sentiment analysis.