It allows the author to express her/his feelings, moods and emotions, and augments a written message with non-verbal elements. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials.Īn emoticon, such as -), is shorthand for a facial expression. There are no patents, products in development or marketed products to declare. Most of the tweets (except English) were collected during a joint project with Gama System ( ), using their PerceptionAnalytics platform ( ). P2-103).Ĭompeting interests: The authors have the following interests: The sentiment annotations were supported by the Goldfinch platform, provided by Sowa Labs ( ) for free. 640772), and by the Slovenian ARRS programme Knowledge Technologies (no. įunding: This work was supported in part by the EC projects SIMPOL (no. Emoji Sentiment Ranking web page, generated from the data is at. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedĭata Availability: Data are available from a public language resource repository CLARIN.SI at. Received: OctoAccepted: NovemPublished: December 7, 2015Ĭopyright: © 2015 Kralj Novak et al. Finally, the paper provides a formalization of sentiment and a novel visualization in the form of a sentiment bar.Ĭitation: Kralj Novak P, Smailović J, Sluban B, Mozetič I (2015) Sentiment of Emojis. Consequently, we propose our Emoji Sentiment Ranking as a European language-independent resource for automated sentiment analysis. We observe no significant differences in the emoji rankings between the 13 languages and the Emoji Sentiment Ranking. Emojis tend to occur at the end of the tweets, and their sentiment polarity increases with the distance. The inter-annotator agreement on the tweets with emojis is higher. The sentiment distribution of the tweets with and without emojis is significantly different. It turns out that most of the emojis are positive, especially the most popular ones. The sentiment analysis of the emojis allows us to draw several interesting conclusions. About 4% of the annotated tweets contain emojis. We engaged 83 human annotators to label over 1.6 million tweets in 13 European languages by the sentiment polarity (negative, neutral, or positive). The sentiment of the emojis is computed from the sentiment of the tweets in which they occur. 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. In contrast to the small number of well-known emoticons that carry clear emotional contents, there are hundreds of emojis. Emojis are Unicode graphic symbols, used as a shorthand to express concepts and ideas. In the past two years, over ten billion emojis were used on Twitter. There is a new generation of emoticons, called emojis, that is increasingly being used in mobile communications and social media.
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