Sentiment of emojis. Novak, P. K., Smailović, J., Sluban, B., Mozetič, I., & Kralj Novak, P. PLoS ONE, 10(12):1–22, 2015. ![Sentiment of emojis [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex There is a new generation of emoticons, called emojis, increasingly used in mobile communications and social media. In the last two years, over ten billion of emojis were used on Twitter. Emojis are Unicode graphic symbols, used as a shorthand to express concepts and ideas. In contrast to a small number of well-known emoticons which carry clear emotional contents, there are hundreds of emojis. But what is their emotional contents? We provide the first emoji sentiment lexicon, called Emoji Sentiment Ranking, and draw a sentiment map of the 751 most frequently used emojis. The sentiment of emojis is computed from the sentiment of tweets in which they occur. We have 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$\backslash$% of the annotated tweets contain emojis. The sentiment analysis of emojis yields 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 emoji rankings between the 13 languages, and propose our Emoji Sentiment Ranking as a European language-independent resource for automated sentiment analysis. Finally, the paper provides a formalization of sentiment and novel visualization in the form of a sentiment bar.
@article{Kralj2015emojis,
abstract = {There is a new generation of emoticons, called emojis, increasingly used in mobile communications and social media. In the last two years, over ten billion of emojis were used on Twitter. Emojis are Unicode graphic symbols, used as a shorthand to express concepts and ideas. In contrast to a small number of well-known emoticons which carry clear emotional contents, there are hundreds of emojis. But what is their emotional contents? We provide the first emoji sentiment lexicon, called Emoji Sentiment Ranking, and draw a sentiment map of the 751 most frequently used emojis. The sentiment of emojis is computed from the sentiment of tweets in which they occur. We have 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$\backslash${\%} of the annotated tweets contain emojis. The sentiment analysis of emojis yields 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 emoji rankings between the 13 languages, and propose our Emoji Sentiment Ranking as a European language-independent resource for automated sentiment analysis. Finally, the paper provides a formalization of sentiment and novel visualization in the form of a sentiment bar.},
archivePrefix = {arXiv},
arxivId = {1509.07761},
author = {Novak, Petra Kralj and Smailovi{\'{c}}, Jasmina and Sluban, Borut and Mozeti{\v{c}}, Igor and {Kralj Novak}, Petra},
doi = {10.1371/journal.pone.0144296},
eprint = {1509.07761},
issn = {19326203},
journal = {PLoS ONE},
keywords = {DOLFINS{\_}T3.1,DOLFINS{\_}WP3},
mendeley-tags = {DOLFINS{\_}T3.1,DOLFINS{\_}WP3},
number = {12},
pages = {1--22},
pmid = {26641093},
title = {{Sentiment of emojis}},
url = {http://dx.doi.org/10.1371/journal.pone.0144296},
volume = {10},
year = {2015}
}
Downloads: 0
{"_id":"jzKPk8NwBk53brx3z","bibbaseid":"novak-smailovi-sluban-mozeti-kraljnovak-sentimentofemojis-2015","downloads":0,"creationDate":"2016-11-22T10:32:19.112Z","title":"Sentiment of emojis","author_short":["Novak, P. K.","Smailović, J.","Sluban, B.","Mozetič, I.","Kralj Novak, P."],"year":2015,"bibtype":"article","biburl":"https://simpolproject.eu/download/Bibliography/DOLFINS2018.06.11v1.bib","bibdata":{"bibtype":"article","type":"article","abstract":"There is a new generation of emoticons, called emojis, increasingly used in mobile communications and social media. In the last two years, over ten billion of emojis were used on Twitter. Emojis are Unicode graphic symbols, used as a shorthand to express concepts and ideas. In contrast to a small number of well-known emoticons which carry clear emotional contents, there are hundreds of emojis. But what is their emotional contents? We provide the first emoji sentiment lexicon, called Emoji Sentiment Ranking, and draw a sentiment map of the 751 most frequently used emojis. The sentiment of emojis is computed from the sentiment of tweets in which they occur. We have 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$\\backslash$% of the annotated tweets contain emojis. The sentiment analysis of emojis yields 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 emoji rankings between the 13 languages, and propose our Emoji Sentiment Ranking as a European language-independent resource for automated sentiment analysis. Finally, the paper provides a formalization of sentiment and novel visualization in the form of a sentiment bar.","archiveprefix":"arXiv","arxivid":"1509.07761","author":[{"propositions":[],"lastnames":["Novak"],"firstnames":["Petra","Kralj"],"suffixes":[]},{"propositions":[],"lastnames":["Smailović"],"firstnames":["Jasmina"],"suffixes":[]},{"propositions":[],"lastnames":["Sluban"],"firstnames":["Borut"],"suffixes":[]},{"propositions":[],"lastnames":["Mozetič"],"firstnames":["Igor"],"suffixes":[]},{"propositions":[],"lastnames":["Kralj Novak"],"firstnames":["Petra"],"suffixes":[]}],"doi":"10.1371/journal.pone.0144296","eprint":"1509.07761","issn":"19326203","journal":"PLoS ONE","keywords":"DOLFINS_T3.1,DOLFINS_WP3","mendeley-tags":"DOLFINS_T3.1,DOLFINS_WP3","number":"12","pages":"1–22","pmid":"26641093","title":"Sentiment of emojis","url":"http://dx.doi.org/10.1371/journal.pone.0144296","volume":"10","year":"2015","bibtex":"@article{Kralj2015emojis,\nabstract = {There is a new generation of emoticons, called emojis, increasingly used in mobile communications and social media. In the last two years, over ten billion of emojis were used on Twitter. Emojis are Unicode graphic symbols, used as a shorthand to express concepts and ideas. In contrast to a small number of well-known emoticons which carry clear emotional contents, there are hundreds of emojis. But what is their emotional contents? We provide the first emoji sentiment lexicon, called Emoji Sentiment Ranking, and draw a sentiment map of the 751 most frequently used emojis. The sentiment of emojis is computed from the sentiment of tweets in which they occur. We have 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$\\backslash${\\%} of the annotated tweets contain emojis. The sentiment analysis of emojis yields 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 emoji rankings between the 13 languages, and propose our Emoji Sentiment Ranking as a European language-independent resource for automated sentiment analysis. Finally, the paper provides a formalization of sentiment and novel visualization in the form of a sentiment bar.},\narchivePrefix = {arXiv},\narxivId = {1509.07761},\nauthor = {Novak, Petra Kralj and Smailovi{\\'{c}}, Jasmina and Sluban, Borut and Mozeti{\\v{c}}, Igor and {Kralj Novak}, Petra},\ndoi = {10.1371/journal.pone.0144296},\neprint = {1509.07761},\nissn = {19326203},\njournal = {PLoS ONE},\nkeywords = {DOLFINS{\\_}T3.1,DOLFINS{\\_}WP3},\nmendeley-tags = {DOLFINS{\\_}T3.1,DOLFINS{\\_}WP3},\nnumber = {12},\npages = {1--22},\npmid = {26641093},\ntitle = {{Sentiment of emojis}},\nurl = {http://dx.doi.org/10.1371/journal.pone.0144296},\nvolume = {10},\nyear = {2015}\n}\n","author_short":["Novak, P. K.","Smailović, J.","Sluban, B.","Mozetič, I.","Kralj Novak, P."],"key":"Kralj2015emojis","id":"Kralj2015emojis","bibbaseid":"novak-smailovi-sluban-mozeti-kraljnovak-sentimentofemojis-2015","role":"author","urls":{"Paper":"http://dx.doi.org/10.1371/journal.pone.0144296"},"keyword":["DOLFINS_T3.1","DOLFINS_WP3"],"downloads":0},"search_terms":["sentiment","emojis","novak","smailović","sluban","mozetič","kralj novak"],"keywords":["dolfins_t3.1","dolfins_wp3"],"authorIDs":[],"dataSources":["JBCT4AXyeopWLaLMW"]}