Sentiment of Emojis
Petra Kralj Novak, Jasmina Smailovi\'c, Borut Sluban, Igor Mozeti\v{c}

TL;DR
This paper introduces the first emoji sentiment lexicon, analyzing over 1.6 million tweets across 13 European languages to map emoji emotional content and propose a language-independent sentiment resource.
Contribution
It presents the Emoji Sentiment Ranking, a novel, language-independent lexicon for emoji sentiment analysis based on large-scale multilingual tweet data.
Findings
Most emojis are positive, especially popular ones.
Sentiment distribution differs significantly between tweets with and without emojis.
Emoji sentiment polarity increases with their position in tweets.
Abstract
There is a new generation of emoticons, called emojis, that is increasingly being used in mobile communications and social media. In the past two years, over ten billion emojis were used on Twitter. Emojis are Unicode graphic symbols, used as a shorthand to express concepts and ideas. In contrast to the small number of well-known emoticons that carry clear emotional contents, there are hundreds of emojis. But what are their emotional contents? We provide the first emoji sentiment lexicon, called the Emoji Sentiment Ranking, and draw a sentiment map of the 751 most frequently used emojis. The sentiment of the emojis is computed from the sentiment of the tweets in which they occur. We engaged 83 human annotators to label over 1.6 million tweets in 13 European languages by the sentiment polarity (negative, neutral, or positive). About 4% of the annotated tweets contain emojis. The…
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