Sentiment of Emojis

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 sentiment analysis of the emojis allows us to draw several interesting conclusions. It turns out that most of the emojis are positive, especially the most popular ones. The sentiment distribution of the tweets with and without emojis is significantly different. The inter-annotator agreement on the tweets with emojis is higher. Emojis tend to occur at the end of the tweets, and their sentiment polarity increases with the distance. We observe no significant differences in the emoji rankings between the 13 languages and the Emoji Sentiment Ranking. Consequently, we propose our Emoji Sentiment Ranking as a European language-independent resource for automated sentiment analysis. Finally, the paper provides a formalization of sentiment and a novel visualization in the form of a sentiment bar.

Fig 1. Top 10 emojis.

Emojis are ordered by the number of occurrences N. The average position ranges from 0 (the beginning of the tweets) to 1 (the end of the tweets). p _c, c ∈ {−1, 0, +1}, are the negativity, neutrality, and positivity, respectively. $\overline{s}$ is the sentiment score.

Fig 2. Sentiment map of the 751 emojis.

Left: negative (red), right: positive (green), top: neutral (yellow). Bubble size is proportional to log₁₀ of the emoji occurrences in the Emoji Sentiment Ranking. Sections A, B, and C are references to the zoomed-in panels in Fig 3.

Fig 3. Emojis in sections A, B, and C of Fig 2.

Shown are emojis that occur at least 100 times in the Emoji Sentiment Ranking. Panel A: negative emojis, panel B: neutral (top) and bipolar (bottom) emojis, panel C: positive emojis.

Fig 4. Distribution of emojis by sentiment score.

The mean sentiment score of the 751 emojis (in bins of 0.05) is +0.305.

Fig 5. Distribution of occurrences and sentiment of the 751 emojis.

The emojis are ranked by their occurrence (log scale). The column color indicates the sentiment score. The partitioning into two equally weighted halfs is indicated by a line at R _1/2. The first 33 emojis are zoomed-in in Fig 6.

Fig 6. Top 33 emojis by occurrence.

Column color represents the emoji sentiment score.

Fig 7. Average positions of the 751 emojis in tweets.

Bubble size is proportional to log₁₀ of the emoji occurrences in the Emoji Sentiment Ranking. Left: the beginning of tweets, right: the end of tweets, bottom: negative (red), top: positive (green).

Fig 8. Negativity, neutrality, and positivity regressed with position (from left to right).

The trendlines are functions p _c(d) of the distance d from the beginning of the tweets.

Fig 9. Sentiment bars of the ‘thumbs down sign’, ‘flushed face’, and ‘chocolate bar’ emojis.

The colored bar extends from −1 to +1, the range of the sentiment score $\overline{s}$. The grey bar is centered at $\overline{s}$ and extended for $\pm 1.96\text{SEM}$, but never beyond the range of $\overline{s}$. Colored parts are proportional to negativity (p ₋, red), neutrality (p ₀, yellow), and positivity (p ₊, green).